Podcasts about gbt

Tell us what you think about this podcast!Bishop Rader Johnson teaches that in the last days, evil men and seducers will grow worse—deceiving others and being deceived themselves. Paul urges Timothy to continue in the truth he's learned. Knowing the Bible isn't enough; we must understand what it means and why it means what it says.Seducing spirits work through people, leading saints away from truth. The only defense is staying rooted in Apostolic teaching and obeying godly counsel. Those who reject sound doctrine and their pastor's guidance open the door to error and destruction.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!Bishop Rader Johnson teaches that in the last days, evil men and seducers will grow worse—deceiving others and being deceived themselves. Paul urges Timothy to continue in the truth he's learned. Knowing the Bible isn't enough; we must understand what it means and why it means what it says.Seducing spirits work through people, leading saints away from truth. The only defense is staying rooted in Apostolic teaching and obeying godly counsel. Those who reject sound doctrine and their pastor's guidance open the door to error and destruction.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In “The Builder,” Bishop Rader Johnson teaches from the foundation scripture found in Matthew 16:13–19 emphasizing that God's church is built upon the revelation of who He is—Jesus Christ. This divine revelation is essential, because it's only by knowing who Jesus is that we can be transformed to be like Him—holy. Holiness cannot be achieved through personal righteousness alone, as in nominal churches; it comes through the New Birth experience, which includes being baptized in the Holy Ghost.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In “The Builder,” Bishop Rader Johnson teaches from the foundation scripture found in Matthew 16:13–19 emphasizing that God's church is built upon the revelation of who He is—Jesus Christ. This divine revelation is essential, because it's only by knowing who Jesus is that we can be transformed to be like Him—holy. Holiness cannot be achieved through personal righteousness alone, as in nominal churches; it comes through the New Birth experience, which includes being baptized in the Holy Ghost.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In “The Builder,” Bishop Rader Johnson teaches from the foundation scripture found in Matthew 16:13–19 emphasizing that God's church is built upon the revelation of who He is—Jesus Christ. This divine revelation is essential, because it's only by knowing who Jesus is that we can be transformed to be like Him—holy. Holiness cannot be achieved through personal righteousness alone, as in nominal churches; it comes through the New Birth experience, which includes being baptized in the Holy Ghost.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In “The Builder,” Bishop Rader Johnson teaches from the foundation scripture found in Matthew 16:13–19 emphasizing that God's church is built upon the revelation of who He is—Jesus Christ. This divine revelation is essential, because it's only by knowing who Jesus is that we can be transformed to be like Him—holy. Holiness cannot be achieved through personal righteousness alone, as in nominal churches; it comes through the New Birth experience, which includes being baptized in the Holy Ghost.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In “The Builder,” Bishop Rader Johnson teaches from the foundation scripture found in Matthew 16:13–19 emphasizing that God's church is built upon the revelation of who He is—Jesus Christ. This divine revelation is essential, because it's only by knowing who Jesus is that we can be transformed to be like Him—holy. Holiness cannot be achieved through personal righteousness alone, as in nominal churches; it comes through the New Birth experience, which includes being baptized in the Holy Ghost.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Reingespielt. steigt in die große Liga auf und entsendet seine beiden Hosts, Amelia4you und PaulShow, als Pressevertretung zum Deutschen Computerspielpreis. Was sie auf ihrem Ausflug ins Palais am Funkturm zwischen Power Armor-Cosplays und Polit-Laudatoren erlebt haben und warum das Essen auf Preisverleihungen schlechter ist als man denkt, erfahrt Ihr in dieser Folge. Außerdem tun Amelia4you und PaulShow noch ihre Schuldigkeit und reden über das Finale von Split Fiction. Time-Codes:00:12 - Vorgespräch (GBT)05:26 - #derDCP202551:24 - Split Fiction - post ludere59:49 - AbschlussSchreibt uns gerne eine E-Mail an ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠reingespieltpodcast@gmail.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Folgt und kontaktiert uns auf Instagram ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@reingespielt_podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Oder schaut vorbei auf ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.reingespielt.de

Think AI is hitting a wall? Nope. This is just the start. Actually, we're at the first chapter. Here's what that means, and how you can move your company ahead. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the conversationUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Generative AI's current phaseMeta's in-house AI chips developmentOpenAI's new developer toolsDay zero of AI and future prospectsReinforcement learning advancementsEmergent reasoning capabilities in AIBusiness implications of AI advancementsAI in healthcare and scienceTimestamps:00:00 Day Zero of AI03:31 AI Tools Enhance Customization & Access09:02 Reinforcement Learning Enhances AI Reasoning11:27 Agentic AI: The Future of Tasks15:59 Tech Potential vs. Everyday Utilization18:48 AI Models Offer Broad Benefits23:15 "Generative AI: Optimism and Oversight"27:08 Generative AI vs. Domain-Specific AI29:24 Superhuman AI: Next FrontierKeywords:Generative AI, Fortune 100 leaders, chat GBT, Microsoft Copilot, enterprise companies, day zero of AI, livestream podcast, free daily newsletter, leveraging AI, capital expenditures, Meta AI chips, Nvidia, Taiwan's TSMC, AI infrastructure investments, Amazon, Google, Microsoft, OpenAI, responses API, agents SDK, legal research, customer support, deep research, agentic AI, supervised learning, reinforcement learning, language models, health care, computational biology, AlphaFold, protein folding prediction.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner

Tell us what you think about this podcast!Offerings are an act of faith, obedience, and sacrifice. In Ezra 1, those who couldn't physically rebuild the temple were still expected to support the work through freewill offerings—the first biblical example of a building fund. God's people are called to give willingly and consistently, as shown in Exodus 36, where the people gave so much that they had to be stopped.Offerings should reflect how God has blessed us (Deut. 16:10)—not based on pressure, but from a grateful heart.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

00:00 - 09:50 - Introduction, UFC, steroids, recent training tales09:50 - 16:01 - How to improve your squeeze strength16:01 - 18:30 - Video games & exercises for sport 18:30 - 21:15 - Seated guard & CrossFit for jiu jitsu 21:15 - 23:00 - Steroids 23:00 - 24:45 - Creatine 24:45 - 29:15 - Strength training for sport and chat GBT 29:15 -35:60 - Hundred men vs Gorilla 35:60 - 41:30 - Unconventional training 41:30 - 45:15 - Biggest meal eaten 45:15 - 47:28 - RNC and closing notes Sponsors: Progress: https://www.progressjj-europe.com Use code RUNESCAPE at checkout for discount on any productsLess Impressed More Involved: https://outlierdb.com/ - use code RUNESCAPE for 50% off your first monthHow to work with us:Charles Strength Training Programs GET 7 DAY FREE MAT STRONG PROGRAM: https://mailchi.mp/charlesallanprice/mat-strong-landing-page BJJ Workouts Instructional: https://bjjfanatics.com/collections/new-releases/products/building-workouts-for-bjj-by-charles-allan-price 1:1 Coaching Inquiries: https://7kdbbkmkmsl.typeform.com/to/nSZHpCOL Eoghan's InstructionalsEoghans Patreon: https://www.patreon.com/eoghanoflanagansubmissiongrappling?fbclid=PAZXh0bgNhZW0CMTEAAaeVwoFHqyoZbzOnBQj1A_HdJuseIdZ5JeBDv2WviMJErMprNx8nBaRtazKB8A_aem_hDebDKTGIEpirScyGQEG0w Leg Lock Instructional: https://bjjfanatics.com/products/leglocks-the-uk-variant-by-eoghan-oflanagan Half Butterfly Instructional: https://bjjfanatics.com/products/down-right-sloppy-half-butterfly-by-eoghan-oflanagan Countering the outside passer: https://bjjfanatics.com/products/sloppy-seconds-countering-the-outside-passer-by-eoghan-o-flanagan Los Banditos Gym: https://losbanditos.club/ Hosted on Acast. See acast.com/privacy for more information.

Tell us what you think about this podcast!Faith is central to the believer's walk with God. It's not just belief—it's substance, though intangible, and it's powerful enough to make what we hope for feel already within reach. True faith isn't in ourselves or our ability to believe—it is faith in God, and it originates from Him. As we learn and grow in His word, our faith is activated and strengthened. For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson expounds on Holiness (defined as "all that God is"). We are taught that in order for us to please God we have to emulate him, we have to live holy. Holiness is an absolute requirement if we are to see God. But first we must understand what holiness is: pleasing God from the heart, being convinced that God's way is right. It involves being committed and our attitude toward God (should be that we love God and we want to please him). Find out more in this important series!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson expounds on Holiness (defined as "all that God is"). We are taught that in order for us to please God we have to emulate him, we have to live holy. Holiness is an absolute requirement if we are to see God. But first we must understand what holiness is: pleasing God from the heart, being convinced that God's way is right. It involves being committed and our attitude toward God (should be that we love God and we want to please him). Find out more in this important series!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson expounds on Holiness (defined as "all that God is"). We are taught that in order for us to please God we have to emulate him, we have to live holy. Holiness is an absolute requirement if we are to see God. But first we must understand what holiness is: pleasing God from the heart, being convinced that God's way is right. It involves being committed and our attitude toward God (should be that we love God and we want to please him). Find out more in this important series!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tyler Woodard offers a simple explanation of AI. Also how to use chat GBT, Grok or gemini for clarification of what you REALLY want to know. And it's true - I called him Taylor the entire time. WHY? You just have to laugh at yourself.

Tell us what you think about this podcast!In this series, Bishop Rader Johnson expounds on Holiness (defined as "all that God is"). We are taught that in order for us to please God we have to emulate him, we have to live holy. Holiness is an absolute requirement if we are to see God. But first we must understand what holiness is: pleasing God from the heart, being convinced that God's way is right. It involves being committed and our attitude toward God (should be that we love God and we want to please him). Find out more in this important series!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Victor Negrescu: [00:00:00] Victor Negrescu este lăsat acolo la Bruxelles pentru că dă o față europeană a PSD-ului. Eu probabil că exprim niște poziții minoritare în partid și recunosc lucrurile acestea dar măcar le exprim am curajul să le spun. George Buhnici: Eu sunt de acord că omul politic trebuie să se ocupe de politică nu trebuie salveze pisici din copac.Victor Negrescu: Nu mă interesează unde se tunde candidatul Sau filmuleţe haioase şi aşa mai departe Sincer nici pisica din copac. Eu nu mă regăsesc. Nu punem la bătaie guvernul se pune la bătaie preşedintele României. Eu cred că se joacă şi soarta guvernării. George Buhnici: Marcel Ciolac o să păţească exact ca Iohannis. O să plece pe sub-autobuz nu cu Victor Negrescu: autobuzul.Dacă Crina Antonescu câştiga alegerile, sunt şase foarte mari Crina Antonescu nu are nicio şansă Este în pinea ta. Dar pe bune, serios, doar atât putem? Doar atât poate PSD-ul? Știu că lumea e coceată pe subiectul ăsta. Și tu insisti, Marcel Ciolacu Marcel Ciolacu, nu e vorba despre el. Nu e despre Marcel Ciolacu este vorba despre George Buhnici: lipsă de educație, incompetență și lipsă de performanță.35 de ani nu s-a întâmplat nimic. Victor Negrescu: Doar George Buhnici: s-a furat. Victor Negrescu: Și pe această chestiune s-a cultivat sentimentul că democrația e de vină și partidele sunt de vină. [00:01:00] Suntem vot împotrivă e bapea mântii, suntem sătui de sistem. Nu e dacă ești suveranist în România. De ce te opui ca ucrainienii să aibă suveranitate? Pentru că dacă tu ești dispus să încalci suveranitatea Ucrainei, cum zic suveraniștii în România, înseamnă că ești dispus să accepti ca Rusia să încalce suveranitatea României.E un nonsens adică când ești George Buhnici: suveranist? Dar le zic nouă suveraniștii că dacă nu am provocat Rusia, Rusia ne-ar lăsa în pace, că noi ajutăm ucrainei și de-aia îi provocăm pe ruși. Spun, domnule, Victor Negrescu: să fim mândri. Adică ei stă acolo să stă cam plecat la Moscova, că asta e problema lor. De George Buhnici: ce ești unul dintre foarte puțini pesediși cu fața umană?Nu uitați să [00:02:00] dați like să lăsați comentariu distribuiți video pe alte ce ești unul dintre foarte puțini pesediși cu fața umană? Acum sper că toată Victor Negrescu: lumea este... Toți politicienii sunt oameni la finalul zilei. Nu știu, mi se pare că, cel puțin în ceea mă privește, că trebuie să vorbesc cât se poate de direct, să fiu eu, să fiu autentic.Fac politică pentru că am niște convingeri ferme. Am trecut și prin situații, zic eu, dificile în politică. Am fost propus de trei ori să fiu exclus din Partidul Social-Democrat și, în consecință, dacă tot am realizat atâția ani, e timpul să vorbim și mai liber și mai deschis și, poate asta mă face mai uman.Când a fost a treia? A treia cu Liviu Dragnea și cu Viorica Năcilă A mi-a fost teamă George Buhnici: ca acum, după turul 1. Vorbeai prea bine. Victor Negrescu: După turul 1 a fost o provocare. Ideea aceasta să fiu comunicatorul [00:03:00] Partidului pentru Alegele Parlamentare am zis că am niște lucruri care, poate unii nu se așteptau să le zic. Și ai rezistat comunicator două zile.Eu zic că nimeni nu s-a dezis, că nu s-a făcut niciun vot. Am fost votat cu unanimitate să fiu comunicator, dar într-adevăr au revenit și alți colegi în prim plan. Însă am spus lucrurile pe care le-am gândit și cred că am contribuit la redresarea partidului social-democrat. Adică tot și-am câștigat alegele parlamentare.Poate unii au mizat și pe mine și pe oameni ca mine că vom conta mai mult. Și da, am spus cum am spus niște lucruri foarte directe. Am spus foarte clar că dacă s-a întâmplat lucrul acesta, nu sunt de acord că a partidul social-democrat să dea votul altui partid în mod special extremiștilor. Și am spus că dacă a făcut cineva lucrul acesta, cu siguranță, în familia social-democrată nu ar trebui să regăsească.Și am spus cu fermitate încă ceva în care cred că noi... Așa spus făcut cineva lucru în că Luptăm pentru [00:04:00] justiție justiție socială În consecință trebuie să fie o temă și pentru noi. Unii au apreciat, alții au apreciat mai puțin. E o dezbatere internă foarte vie în Partidul Social-Democrat și în sensul acesta nu a zice că există tabere, nu e valoare de tabere, dar e normal să existe și viziuni diferite și fiecare să contribuie cum dorește la această direcție a stângii românești.George Buhnici: După interviul de la ProTV, m-am convins că vreau să am o conversație cu tine. Și după aia ai dispărut. Și a fost foarte ciudat pentru că, exact cum ai zis tu ai spus ceea gândeai, dar ai spus ceea ce gândeam mai mulți. Și era una dintre rarele ocazii când nu mă uitam la un lider politic de la orice partid din România, care vorbea ok.Că nu mă aștept la performanță excepțională de la politicienii români, dar vorbeai ok. Încă... Acum înțeleg mai bine că ai vorbit împotriva conducerii. Victor Negrescu: Nu, nu nu. George Buhnici: Dacă trebuie să iasă cei care au dat voturi, a ieșit la iveală [00:05:00] ulterior că șefii PSD-ului au trimis oamenii să dea voturi lui George Simion.Victor Negrescu: Nici nu mai înțelegem dacă a fost o glumă sau nu a fost o glumă. Acum nu știu. Adevărul este că Partidul Social-Democrat nu a prins turul 2 și trebuie să ne dăm seama că au fost comise cel puțin niște greșeli strategice și ar fi foarte ușor pentru mine să spun că X sau Y este responsabil. O spun foarte direct.E o responsabilitate comună A Partiului Social-Democrat pentru ceea ce s-a întâmplat anul trecut și pentru partidari și pentru România, că de fapt România a avut de suferit pe prisma faptului că, iată, un candidat extremist era să ajungă președintele României cu o agenda, cred eu, împotriva românilor.Așa că tot din interiorul acestui partid trebuie vină soluția pentru a se redresa. E nevoie de o stângă puternică în România, una autentică, sinceră deschisă pentru că [00:06:00] peste toată lumea se așteaptă de la stânga să facă mult mai mult decât toată lumea pentru că noi de principiu spunem reprezentăm oamenii.Complicat adică nivelul de presiune este mult mai mare, standardele sunt mult mai ridicate și trebuie să învățăm și noi cum să respectăm acest angajament pentru că altfel, da, se va întâmpla ca în multe zone din Europa. Stânga românească va avea de suferit dacă nu se adaptează și dacă nu este cu adevărat umană și sinceră.George Buhnici: Eu cred că până la următoarea alegeri în ritmul actual, PSD-ul se va toci de tot și nu este singurul care va avea problema asta. Ce se întâmplă acum nu este un accident. Și acum, într-adevăr stai și te uiți băi ok, avem nevoie de stânga, dar până când să avem, să ajungem să vorbim de ce înseamnă stânga ce înseamnă să fii social-democrat că aș vrea să aud lucrurile astea de la un PSD-s până în urmă, de altfel primul care vine aici, am vrut să aduc și pe domnul Ciolacu înainte de alegeri doar că nu merge decât la chestii aranjate.În condițiile actuale cu Partidul Social-Democrat în formă asta, [00:07:00] eu nu știu ce mai rămâne după alegerile prezidențiale pentru că, da, acum există o coaliție care are guvernul aranjat. Oamenii înțeleg prea puțin lucrul ăsta. Nu punem la bătaie guvernul, se pune la bătaie președintele României. Corect?Partea asta de coaliție de guvernare este pare rezolvată, dar eu nu văd bine liderii niciunui dintre partidele astea două care controlează această coaliție. Da, eu Victor Negrescu: cred că se joacă și soarta guvernării deși cu siguranță mi-aș dori să discutăm mai mult despre ce fel de președinte ne dorim pentru România și care sunt proiectele lor.Acum toată lumea e pe TikTok. E foarte bine, mă bucur să aflăm mai multe despre candidații la prezidențială, însă mi se pare totul forțat. Care-i proiectul de țară? Sincer, poate e profilul meu un pic mai serios. Nu mă interesează unde se tunde candidatul sau filmulețe. Eu nu mă regăsesc Cu siguranță și ăsta este un exemplu [00:08:00] Dar cred că acum avem nevoie, culmea, într-un moment dificil de politicieni serioși care își asumă acest rol.Responsabilitatea pe care o au. Eu am o chestiune. Sincer dacă... Dimineață nu am un program plin și nu fac ceea ce mi-am propus și nu am niște rezultate la finalul zilei, da, am un sentiment de rușine. Asta mă încearcă Adică, totuși, oamenii m-au votat, sunt plătiti din bani publici recunosc lucrul ăsta, deci am o misiune.Unii spun că exagerez, că sunt de principiu mai workaholic în felul acesta. Deci trebuie să ne facem treaba și asta vor oamenii să vadă de la noi. Toată lumea zice, dom'le, trebuie să fim umani. Eu nu înțeleg chestiunea asta. Omul politic care vrea să fie uman. Păi dacă ești om politic, ești, în primul rând om și prin ceea ce faci arăți că te preocupi de ceilalți.Dar alegerile acestea sunt cruciale. Cruciale pentru... George Buhnici: Până la alegerile cruciale hai să vorbim un pic de chestia asta umană, că e o capcană. Eu sunt de acord că omul politic trebuie să se ocupe de [00:09:00] politică nu trebuie să salveze pisici din copac ca să fie cool pe TikTok și nici să-mi arată unde se tunde sau ce am mâncat sau chestii genul ăsta.Astea sunt populisme. Putem fi de acord? Da, sunt total de acord. Putem fi de acord că să fii politician este o meserie în sine și nu trebuie fii entertainer? Victor Negrescu: Sunt de curge aici. Aici problema aceasta, această confuzie între entertainer și politician ne dus în situația pe care o trebuie să mă astăzi. Și da, partidele mainstream au făcut această greșeală au căutat să copieze.Au fost câteva exemple de oameni care au reușit fiind mai degrabă cum spui tu, entertainer decât să fie altceva și în contextul acesta s-a copiat acest model. Însă e vorba de responsabilitate. Dacă țipi nu faci o legie bună. Dacă eventual faci un clip high-ost, asta nu înseamnă că ai stat în comisie și ai negociat decizia cea mai bună.Plus pentru a lua o decizie bună trebuie să te consulti cu mediul de afaceri, cu sindicatele. Trebuie să o scrii, să te discuți cu specialiști să [00:10:00] negociezi cu o altă partidă. Știu nu e fan chestiunea asta. Știu și oamenii care se uită acum la noi, se gândesc doamne, ne dău Victor Negrescu lecții de moral acum.Le știe el pe toate. Nu le știu pe toate. Însă nu-mi doresc să fiu acest tip de politiciar și nu cred că este direcția corectă nici pentru România nici pentru Europa să facem lucrurile acestea Și ca să dau un exemplu că există acest model și la nivel european. Și spun foarte deschis, eu ca pro-european convins.Nu mă interesează când Ursula Van der Leyen, președinta Comisiei Europene, merge la o reunie în Brazilia și mi-arată clip pe Instagram ca să pară cool că s-a dus pe plaja din Brazilia și s-a întâlnit cu oamenii când alerga de dimineață. Nu cred că asta trebuie să facă că trebuie să fim umani, să interacționăm, să fim disponibili, să mergem în supermarket, să ne punem benzină să orice, lucrurile astea trebuie să le facem, în mod natural.Dar este natural să ai o cameră după tine când faci toate lucrurile astea? Nu mi se pare atât de naturală chestia asta. Apoi, de niște mii George Buhnici: euro. Și unii și alții. Deci putem fi de acord [00:11:00] că avem nevoie de politicieni profesioniști când fac chestia asta, problema pe care o văd însă este că oamenii sunt sătuli de elite și percep politicienii de carieră și tu ești unul, Ca fiind niște elite decuplată de la realitate.Și acum și tu ești la treilea mandat în Parlamentul European, faci parte din elita asta. Faptul că vii și îmi spui într-adevăr că sunt uman dar nu vreau să fiu entertainer, asta nu înseamnă că nu faci parte din elita politică. Victor Negrescu: Acum depinde și cum ne gândim la această elită. În istoria României au fost niște lideri politici care și-au asumat responsabilități.Și ții minte că cel puțin noi românii suntem mândri de deciziile luate de anumiti lideri politici care erau tot... Politicieni între ghinimele de carieră Cum eu sunt, în primul rând cadru didact, profesor, așa mă definesc Și, evident, fac și politică de multă vreme, luptându-mă pentru niște convingeri. E nevoie de experiență, de expertiză e nevoie de contact, e nevoie de toate aceste aspecte pentru [00:12:00] a avea impactul dorit.Adică nu e ca și cum astăzi intri în politică și dintr-o dată schimbi ceva sau știi cum funcționează lucrurile. De altfel un om care nu înțelege mecanismele nu va fi eficient, nu va produce rezultate. Însă încerc să păstrez ceea ai spus tu foarte bine, contactul uman Eu am o organizație în interiorul Partiului Social Democrat compusă din peste 10.000 de persoane, persoane care sunt fie membri fie simpatizați de stânga, pro-europeni, Mai tineri în general, dar nu doar tineri și împreună cu ei, periodic, facem o serie de acțiuni inclusiv acțiuni cu caracter social, care sunt diferite.Știți cum se spune de obicei, partidele merg cu plasa, de exemplu la oameni și așa mai departe, inclusiv când fac acțiuni caritabile. Și e bine să fie acțiuni caritabile. La noi facem aceste tipuri de acțiuni dar diferit De exemplu mergem deja de aproape 10 ani, în fiecare an, la copii din zone defavorizate dar pe lângă Că cadourile pe care le [00:13:00] facem, stăm cu ei, împodobim bradul, discutăm aflăm care e problema și facem și follow-up.Și mai invităm și oameni din comunitate, profesori cunoscuți medici oameni politici să vină cu noi. Și aceste experiențe umane, și pentru mine spun sincer, dar și pentru colegii mei ne ajută pe toți să relativizăm, să ne dăm seama. Adică am fost într-un cartier din Sibiu, erau numai vile și în mijloc era un granș în care stăteau șapte fetițe cu familia lor.Am fost de exemplu în Vrancea și la un moment dat, tot așa într-un loc părăsit de lume, o familie formată din două persoane care au crescut într-un centru pentru copii, s-au instalat acolo într-o casă părăsită aveau doi copii și trăiau în aceeași încăpere cu o vacă Știu, pare straniu și am încercat să găsim soluții, să le găsim o casă, să le găsim un loc de muncă, să vedem cum copiii pot merge la școală, unii s-au decuplat asta cred că trebuie să facem mai mult sincer eu, i-aș duce pe mulți [00:14:00] politicieni în aceste zone să vadă la firul ierbii pentru că unele politici nu funcționează până jos și aici cred că e problema neîncrederii față de politică în România, lumea aude lucruri frumoase, vorbim de miliarde de euro europeni, vorbim de decizii merge, bubuie economia și oamenii la firul ierbii nu simt nu este vina doar a decidenților politici, însă mai multă atenție la implementare ar ajuta foarte mult George Buhnici: practic asta este decuplarea când te uiți către Bruxelles nu te uiți la nivel ochelor te uiți în sus și este și o diferență de distanță și de nivel și într-adevăr oamenii simpli nu văd întotdeauna beneficiile astea deși de foarte multe ori punga aia care vine de la primărie era de fapt trimisă de Uniunea Europeană și sunt multe lucruri care se schimbă în viețile noastre datorită Uniunii Europene La revedere!Cei din orașe și mai ales audiența mea înțeleg chestia asta. Eu vreau să înțeleg aici care e, până la urmă, strategia lui Victor Negrescu, pentru că e deja la al treilea mandat în Parlamentul European. Acum ești vicepreședinte. Înainte să faci 40, [00:15:00] nu? Faci la vară. La vară fac. Un vicepreședinte foarte tânăr de Parlamentul European, un politician de carieră Care ți-e planul?Ce vrei de fapt? Victor Negrescu: Vreau să lași ceva în urmă. Vreau să am un impact. La 40? Da La 40 de ani e o problemă chestiunea asta. Când am intrat prima oară în politică mi s-a spus că sunt prea tânăr. Am fost cel mai tânăr român ales vreodată în Parlamentul European și atunci mi s-a spus că sunt prea tânăr. Am intrat din întâmplare pentru că m-au pus pe un loc neeligibil, însă am intrat.Și al doilea mandat tot din întâmplare pentru că am intrat după Brexit. Și după aceea poți să te și scoate. A fi lasat mă și scoată, da. Al treilea mandat zicem că a fost mai ușor un pic, dar ne-a lău obținut și automat a rezultat și în poziția pe care am câștigat-o de vicepreședinte al Parlamentului European.Dar vreau să las ceva în urmă. Când mi este foarte greu și într-un unghi personal și, pe urmă, spun și zona politică, mi-e foarte greu să explic băiatului meu de 12-10 ani de ce m-a văzut mai [00:16:00] rar Dacă nu pot să-i spun că am făcut ceva și că sunt niște rezultate. Am nevoie de chestiunea asta, simt și asta cred că pot să fac astăzi Am puterea resursele, relațiile, dorința să fac lucrul acesta, dar dintr-o perspectivă mai largă cred că e nevoie de lider și pasumat, mai ales pentru ceea ce înseamnă astăzi drumul României.Care-i viziunea? Pentru că noi suntem generația, mă înțeles că suntem de o vârstă destul de apropiată, chiar dacă ești puțin mai în vârstă, noi suntem generația acelor care au vrut să reușească pentru că au văzut greutățile prin care au trecut poate părinții noștri și am vrut și mai mult decât ei, am vrut să reușim, am vrut să ne fie mai bine și să fie mai bine poate și copiilor noștri și ne-am luptat, ne-am luptat, ne-am luptat, dar proiectul nostru a fost aderăm la Uniunea Europeană, aderăm la NATO și care următorul proiect de țară Ce se întâmplă?Pentru că sunt niște schimbări profunde și știi noi ne mândrim sectorul digital în România, e beton suntem tari Au o problemă în sectorul judicial în România, nu mai ține pasul cu tendințele. Vorbim, [00:17:00] agroalimentar agricultura românească e performantă. În alte domenii nu mai este atât de performantă. Cum ține pasul?E clar că trebuie o altă viziune și oameni să se implice. Și îndemnul meu, inclusiv către cei care se uită, este să se implice. Este o lipsă de implicare. Suntem pe ultimele locuri la nivelul european în ce înseamnă implicarea civică a oamenilor. Nu neapărat în politică deși ideal este în politică, dar pentru a putea să alegem oameni competenți trebuie să fie concurență Eu spun.Cum poți George Buhnici: să te concurezi cu Ciolacu și cu Stănescu în PSD cu, nu știu, ăștia toată clica din PNL. În fiecare partid există cât un aparat din ăsta. Dacă vrei să te implici în politică, te uiți și vezi că intri, de fapt nu intri într-un partid intri într-o organizație. Și aș putea să adaug după mafiotă o organizație pe bază de interes sau o organizație opacă în care meritocrația...Serios, acum, încă o dată, îmi pare rău că trebuie să spun lucrul ăsta. Bă dar când arată domnul Ciolacu diploma aia de [00:18:00] bacaloreat? Știi? Și când aud, pe exemplu noi înregistrăm pe final de martie, deja au început să apară fisurile comunicării cu președintele pe subiectul ministrului de externe. Astăzi se decide în timpul discuției noastre, soarta ministrului de externe, că primul nostru ministru ar vrea să o dea la pace, cumva, cu americanii.Pe partea cealaltă președintele spune, hai să nu ne criticăm oamenii în public. Victor Negrescu: Acum Ce fel de leadership e ăsta? Eu cred și în responsabilități și răspundere individuale. Totuși, așa funcționează lucrurile, dar în același timp... Partidele au rostul lor într-o democrație Ele organizează ideile Organizează participarea la decizii Care e ideea?Care e ideea la PSD? Ideea de stânga există Totuși Partidul Social-Democrat Social-Democratia în România Are 132 de ani de istorie Atunci a apărut primul Partid Social-Democrat În România Știu că cei de dreapta spun că ei sunt [00:19:00] Istoria României, însă Social-Democratii în România Au contribuit foarte mult La dezvoltarea României moderne Mulți ignoră faptul că atunci când s-a realizat Marea Unire a fost un fel de adunare Parlamentară în Transilvania Și jumătate din cei care au votat din parlamentarii Respectiv erau Social-Democrati Culmea în Transilvania unde PSD Nu are rezultate tocmai bune Și sunt exemple de acest fel de Social-Democrati Care au contribuit la istoria noastră S-au luptat și cu comuniștii, comuniștii i-au trimis la închisoare Și naziștii i-au trimis la închisoare Pe Social-Democrati și dacă mergem În închisorile comuniste Sau...Extremiste din România, naziste, vedem da, acolo practic zonă unde au murit socialdemocrati. Zici, se uită lucrul acesta. Eu cred în această tradiție, în această istorie. E singurul partid socialdemocrat în România și pentru asta mă lupt. E o concurență, o competiție un conflict de idei, ar fi foarte simplu acum să spun că X este greu.Eu am o comunicare, zic eu, bună cu Marcel Ciolacu atunci [00:20:00] când sunt consultat pe niște subiecte. Și nu este doar de acum. Pe-a lungul timpului împreună am lucrat în a schimba poate modul în care Partidul Socialdemocrat a comunicat pe zona europeană. Era foarte izolat pe plan extern, acum nu mai este atât de izolat.Însă revenind la contextul pe care îl spui acum, Eu cred că avem deficiențe inclusiv din punct de vedere constituțional, în modul în care este reprezentată România pe zona de politică externă. O să pară critică la adesa cuiva, din nou nu-i adesa la cuiva, e o critică constructivă și structurală. În cazul României, reprezentantul României la Consiliul European este șeful statului.Șeful statului nu poate interveni în politica internă. 90% din deciziile importante luate la Bruxelles privesc politica internă, politica pentru consumatori, politica agricolă, banii europei, subiectele ce țin de investițiile în zona de industrie de apărare, culmea, e tot politica internă. De-aia se [00:21:00] duce cu ministrul de externe, George Buhnici: se duce cu Victor Negrescu: reprezentanții guvernului, nu?Dar a fost cu ministrul de externe? Domnul Curezeanu a fost acum în perioada aceasta la Consiliul European sau la ședințele cu liderii europeni. De exemplu eu îl cunosc pe domnul Curezeanu, am un respect deosebit, am lucrat împreună pentru ca să deblocăm poziția austriei. Pe domnul Bolojan l-am văzut în multe poze.Pe domnul Bolojan l-am văzut la toate chestiile astea. Dar n-a fost împreună cu președintele Ar fi normal ca ministrul de externe să meargă cu președintele. Pentru că politica externă este responsabilitatea președintului. Și să meargă împreună. Cum mergi și alții? Deci nu se înțeleg care e problema. Nu știu eu cred că și acolo te-ai văzut un pic care este coordonarea.În moment trăim un moment în care trebuie să fim mult mai eficienți pe zona de politică externă. Și cred că fiecare are rolul lui. De exemplu pe domnul Hurețanul L-aș folosi, e urât că spun lucrul ăsta, dar l-aș folosi, sincer, pe relația aceasta cu Germania, nouul guvern din Germania, cu relația poate cu nouul guvern din Austria, e foarte bun, poate inclusiv pe subiectele europene.Cu siguranță avem niște carențe în relația noastră cu alte state, fie că vorbim de Statele Unite sau că vorbim de India, care acum [00:22:00] este noua pole economică al lumei. Este cea mai mare națiune a planetei. Da, și ați văzut cum se duc liderii europeni din toată lumea, merg în India pentru contracte, pentru a dezvolta relații de afaceri sau politice.Noi nu existăm. Și clar că ne trebuie niște persoane care au niște uși deschise. În același timp putem pretinde că cineva trebuie să-și deschide ușile așa dintr-o dată Este și o construcție. Eu mă uit, de exemplu la prietenii mei laboriști din Marea Britanie. Până să ajungă Să câștige guvernarea, cei de stânga din Marea Britanie au avut persoane desemnate pentru a învăța și ministrul lor de externe, înainte să facă lucrul acesta ajunge în poziția aceasta, a mers și a discutat În toată lumea, inclusiv în România, a avut discuții la nivel înalt pentru a înțelege.Nu pentru a spune ce gândește sau a prezenta ceva, pentru a înțelege contextul în așa fel încât în momentul în care ajunge funcția respectivă să fie pregătit. Noi aici nu pregătim, deci noi nu avem rezerve, o să sună aiurea, rezerve de cadre [00:23:00] politice. Nu profesionalizăm. Partidul Social-Democrat, care de principiu este cel mai pregătit partid din România din punctul ăsta de vedere, nu mai are aceste...Pentru că te uiți în George Buhnici: sus și când te uiți acolo în vorb, zici bă nu e ceva ce mă așteptam să fie la vârful unui partid în care aș vrea să mă regăsesc Dacă mă uit la stânga și aș alege PSD-ul, pentru că am cunoscut oameni foarte competenți, foarte deștepți, care mi-au spus, zici George, te-am mai auzit vorbind despre noi PSD-ul, zici, dar uite un pic ce fel de oameni sunt, pentru că avem oameni competenți mulți între ei sunt antreprenori într-un partid social-democrat.Și am dat dreptate. Dar cu toate astea O fi o rezervă de cadre undeva pe acolo Bă dar la vârf Bă, pe bune, serios, doar atât Victor Negrescu: putem Doar George Buhnici: atât poate Victor Negrescu: PSD-ul? Știu, țintim sus, dar ar fi atât simplu să fie doar o chestiune de vârf Eu cred că e o problemă la bază în ansamblu pentru partide. Modul de selecție, modul în care [00:24:00] cresc oamenii în partidele politice.Nu vreau să mă prezint eu ca o excepție. Eu știu de ce am rezistat în politic. Am rezistat pentru că am creat această organizație cu 10.000 de oameni și pentru că am avut posibilitatea să mă întăresc poziția în partid prin prisma rolului meu la nivel european Am construit foarte mult la nivel european, contacte nu doar la nivel european și poate a zice internațional, cu tot ce înseamnă mișcări de stânga sau democratice.Și în contextul acesta, acest lucru mi-a primit să rezist. Dar altfel ar fi fost foarte greu Trebuie mai multe exemple în acest fel și mai multă presiune de jos în sus, mai multă concurență. Sincer acolo este problema. Spuneam mai devreme, pe categoria mea de vârstă, în toate partidele politice, nu suntem foarte mulți.Eu nu simt o mare presiune, o mare concurență. Când am intrat prima oară în Partidul Social-Democrat, recunosc, mi-era cam frică și cu privire la șansele mele de reușită, dar și când mergeam într-o ședință [00:25:00] a conducirii Partidului Social-Democrat, nu prea vorbeai. Nu pentru că neapărat erai de acord cu ce spuneau ceilalți, dar aveau mult dintre ei o carieră în spate, erau de foarte mult timp, aveau argumente în a susține poziția din nou cu care puteam să nu fiu de acord.Acum lucrurile sunt mai prea relaxante Relaxate. Inclusiv în dialogul între partide. Când am o dispută de idei cu cineva de la alt partid... Parcă nu merge până la capăt cu argumentele Nu zic că este ușor, că nu este ușor dar înainte să vin la această emisiune spuneam că m-am întâlnit cu 2000 de tineri online, conectați în toată Europa și mi-au pus niște întrebări.Wow, ce întrebări! M-au întrebat întrebări grele. De ce se votează europarlamentari care nu au legătură cu Parlamentul European? De exemplu care este poziția Parlamentului European pe subiectul legat de avort? De ce nu se face mai mult pe educație? Sunt cazurile de corupție la Parlamentul European în partidele mainstream?Sunt toți corupți? Adică întrebări serioase. La care trebuie să fie [00:26:00] răspuns? Uneori e convins sau nu. Dar în politică noi nu discutăm lucrurile astea Adică sunt generalități și prin prisma faptului că nu e conținut, nu e substanță Și mai ales convingeri. De ce fac oamenii ăștia politică? Eu am un răspuns la întrebarea asta, dar eu cred că dacă mai ai politicieni aici, de acum o să pară forțat dacă mă întrebi pe mine, întreabă-te rău frumos de ce fac politică.Eu am remarcat că sunt foarte mulți oameni în politică în România care nu au un răspuns sincer la această întrebare sau nu un răspuns care are legătură cu cetățenii și e grav lucrul ăsta. George Buhnici: Revenim la IGDLCC în dată ce-ți spun despre sponsorul nostru, Darkom Energy, cei care ne garantează că nu ni se sting luminile din studio, adică nu avem niciodată pene de curent.Panourile fotovoltaice, invertoarele și bateriile sunt inima sistemului nostru energetic și cred cu tărie că sunt investiții importante, dar și rentabile. Cu acest sistem am economisit deja mii de euro la facturi, dar și mai important avem electricitatea garantată fără fluctuații care ne pot defecta [00:27:00] energiile Dacă ai în plan să construiești, să renovezi orice fel de clădire, inclusiv industrială, alege o soluție solidă de generare și stocare de energie Noi colaborăm cu echipa Darcom Energy și îi recomandăm.Eu cred că există o dezorientare totală în partidul vostru, pentru că pe de o parte, tu ești văzut, cel puțin asta e percepția din documentarea mea, Victor Negrescu este lăsat acolo la Bruxelles pentru că dă o față europeană PSD-ului și face să pară un pic mai sus decât e, în realitate. Iar aici la nivel local, e o mare problemă într-adevăr de competență, de cadre, pentru că structura de conducere a ajuns să fie...Nu știu cum să zic, parazitată, căpușată controlată de o mână de oameni extrem de puternici extrem de influenți și în niciun caz orientați pe meritocrație. Victor Negrescu: Mi s-a părut interesant ce ai zis cu această pară mai sus decât e. Eu spun foarte clar, [00:28:00] chiar dacă trec pe legă trei excluderi din partid. Probabil că oameni ca mine sau inclusiv eu putem să dispărem oricând din politică.Partidul este foarte ușor să scape de mine. Eu probabil că exprim niște poziții minoritare în partid și recunosc lucrurile acestea dar măcar le exprim am curajul să le spun mai des în interior, mai rar public pentru că eu cred foarte mult în discuțiile interne, uneori cu rost alte ori nu Ce vorbeam mai devreme George Buhnici: de discuție dintre primul ministru și ministrul de externe, care se întâmplă în public.Victor Negrescu: Nu este foarte eficientă această dispută publică totuși că s-au întâlnit și în privat. Totodată o coaliție este greu de gestionat și cine stabilește ministrul de externe, din ce mi-aduc aminte, a fost mai ales domnul Hurezeanu, a ajuns în această funcție cu sprijinul fostului președinte a României. Și poate și aici a apars incopelea asta, pentru că ministrul de externe trebuie să fie legătura între premier și președinte, cred că acolo e rolul lui.Dacă nu poate exercita acest rol, sunt niște George Buhnici: [00:29:00] dificultăți. Nu vreau să sap prea mult pe subiectul ăla cel mai probabil până ajungem noi să publicăm, să va fi rezolvat cazul ăsta, dar e interesant așa ca timestamp ca moment în timp pentru toată discuția asta. Ce mă preocupă însă pe mine este, aș vrea să înțeleg dacă în interiorul PSD se înțelege cât gravă este problema, pentru că eu nu cred...Că nici măcar nucleul dur al partidului mai rezistă până la următoarele parlamentare în ritmul ăsta. Victor Negrescu: Eu sunt un pic mai optimist aici, pentru că cred că avem oameni buni și oameni care au performat mai ales în administrațiile locale. Ok o să mă arunc eu George Buhnici: și o să zic Dacă nu se întâmplă până la prezidențiale, imediat după, Marcel Ciolac o să pățească exact ca Iohannis O să plece pe sub-autobuz nu cu Victor Negrescu: autobuzul.Dacă Crin Antonescu câștiga alegerile, sunt șase foarte mari ca Marcel Ciolacu să-și continue mandatul în fruntea guvernului. Crin Antonescu nu are nicio șansă. Este opinia ta. Mulți din partidele... Știu partidele George Buhnici: în [00:30:00] PSD și în PNL este ordin pe Victor Negrescu: unitate Toată lumea subține pe Crin Antonescu. Cred chestiunea aceasta.Acum... Plecând de la chestiunea aceasta pe care tu ai subliniat-o, e o problemă gravă Nici nu știi care este soluția corectă în contextul actual, extrem de dificil. Și din nou revenim la responsabilitate la ce facem. Miza nu este unul. Miza este ce faci mai departe Care este proiectul? Ne George Buhnici: agățăm de oameni.Asta e și motivul pentru care suntem astăzi aici. Ne agățăm de oameni. Eu m-am uitat că nu poți să îngropi un partid social-democrat. Ai nevoie de stânga. Da cum ai zis și tu. Victor Negrescu: Hai să-ți dau un exemplu. Eu am fost doi ani ministru cel care a pregătit președinția României la Consiliul European, în momentul unde am performat ca țară.Și când eram ministru, automat, ocupându-mă de afaceri europene, mai plecam să mă întâlnesc cu demnitarii alte state. Și când plecam, automat... Dacă funcționarii veneau fie [00:31:00] mai târziu la birou, fie pur și simplu nu realizau sarcinile în timp util, tot sistemul din România este crăionat în jurul omului. Dacă ministru e bun și eficient, se întâmplă ceva.Dacă ministru e prezent la birou, se mișcă lucrurile. Dacă are un cabinet puternic, automat se mișcă lucrurile. Ceea nu e normal. Lucrurile trebuie să funcționeze de la sine. Știi, în Belgia au avut luni bune fără guvern și statul a funcționat. Asta înseamnă un stat puternic și serios, care funcționează efectiv poate cu un aport al politicilor în care dau direcția, dar care poate funcționa măcar pe lucrurile de bază fără nicio fel problemă.Ori noi avem multe rateuri, inclusiv la aceste chestiuni de follow-up, fonduri europene pe care le ratăm, termene europene pe care le ratăm, implementarea unor directive europene. Ori avem multe rateuri, aceste chestiuni de-up fonduri ratăm europene Wow, din nou o să zic că expun toate problemele astea, le știm cu toții.Dar înțelege George Buhnici: PSD-ul profund, PSD-ul, structura de [00:32:00] conducere a partidului, înțelege cea mai mare bucată din responsabilitate în care primul ministru... Victor Negrescu: Eu cred că în Partidul Social-Democrat se înțelege lucrul acesta și vă spun foarte bine că este multă liniște cel puțin în spațiu public, dar noi în interior, cel puțin eu am făcut-o, am avut discuții cu premierul României, am spus opinia mea și câteva idei pe care le-am, mai ales pe zona aceasta de politică externă la finalul zilei el este cel care decide.Totuși a reușit să formeze o coaliție de guvernare într-un context dificil are acest parteneria cu domnul Bolojan, au stabilit un candidat comun, este o responsabilitate comună a liderilor acestor partide, au gândit această formulă, ne putem întreba e cea mai bună, nu e cea mai bună formulă asta este formula pe care aceste partide au găsit-o, sincer sper să funcționeze.E o cotă ceală, speri tu speri, nu ești sigur E o cotărceală românească. Cred că e foarte greu să fii sigur după ce s întâmplat anul trecut. [00:33:00] Totuși, candidatul nostru era pe primul loc în toate sondajele de opinie și nu a ajuns într-unul doi. Deci lucrurile se pot schimba dramatic. Și din punctul ăsta de vedere, trebuie să avem un nivel de precauție.Însă responsabilitatea noastră a celor din mediul politic depășește ciclul electoral sau momentul electoral. Eu am înțeles, mentuși aici, cred că și dezamăgirea pe care o văd la mulți oameni. Politicienii dau impresia că ei se preocupă de cetățeni doar că sunt alegeri Și acum e același sentiment. Eu am impresia că astăzi trăim din nou toamna anului trecut.Asta cred eu. Nu George Buhnici: este un purgatoriu este ceva nesfârșit așa Deci este, nu știu, de jumătate de ani suntem în limbo. Victor Negrescu: Da, și liniștea socială ascunde, de fapt, aceleași riscuri ca și anul trecut. Un vot protest, un vot bazat pe agresivitate, pe supărare și dacă nu sunt canalizate aceste [00:34:00] energii într-un sens pozitiv către o soluție de speranță cu proiecte concrete, va fi foarte complicat.Din nou, mulți dintre cei angrenați în această campanie prezidențială și, din nou am vorbit inclusiv cu Crina Tonescu, dau sentimentul că ei candidează Pentru a vorbi despre politică. Președintele nu trebuie facă mai mult decât politică. De aceea și Constituționalul are rolul ăsta să fie deasupra partidelor.Trebuie să văd că despre cetățeni. Eu, dacă mergi, m-am întâlnit de exemplu, recent cu tineri într-un liceu chiar din București. Merg prin toată țara și am întrebat pe tineri care este principala lor preocupare și mi-au zis noi învățăm ceva aici și nu știi dacă vom găsi un loc de muncă. Exact. Că am înțeles că locurile noastre de muncă vor dispărea.Ei studiau, elevii aceștia, o filiară profesională. Unii în zona auto, ceilalți în zona de contabilitate și mă întrebau. Eu folosesc ei spuneau noi folosim cea GBT și alte instrumente AI [00:35:00] și fac cam ceea ce învăț eu aici. O să am un job? Asta mă întrebau. De ce nu vorbim de subiectele astea? De ce nu atingem subiectele dificile, care nu necesită neapărat o soluție ușoară?Adică politicienii evită să aleg numai ce este confortabil. Și de aceea cred că suntem situația asta, pentru că confortul dezbaturilor publice a făcut ca oamenii să nu se mai simtă reprezentati sau să nu mai simtă că ideile lor sunt discutate sau o preocupare pentru cei care decid. George Buhnici: Da Singurul candidat pe care l-am auzit vorbind despre tehnologie, inteligență artificială, digitalizare, educație, toate lucrurile astea, era Mircea Joana.Nici nu a contat întoruntei pentru că el nu a înțeles cât importantă era emoția la un moment dat respectiv, pentru că este exact ce ai zis este vot împotrivă. E bapea mătii, suntem sătui de sistem, whatever that is, de statul profund, dar eu nu cred, încă o dată, că oamenii din partidele de la putere înțeleg asta.Că problema nu s-a [00:36:00] rezolvat doar că l-ai pus pe Bolojan acolo care vorbește frumos. Nu-i ajuns. Victor Negrescu: Da, nu este cu siguranță de ajuns și chiar dacă acum... Există această încredere că nu se m-au mai întâmplat ce s-a întâmplat anul trecut și sondajele și sentimentele conduc la această impresie. Asta nu înseamnă că peste patru ani sau cinci ani nu ne vom regăsi în acea situație.Va fi mai rău. Și eu cred la fel. Dacă nu se întâmplă ceva. Pentru că eu am remarcat, sunt foarte atent la ce se întâmplă Și nu rezolvăm cu închiderea TikTok-ului în timpul alegerilor? Cu siguranță nu asta este soluția, dar în alte state europene, cea mai mare provocare nu a fost prima generație de extremiști.A doua și a treia generație, care a ajuns la performanță electorală. În Italia există data legile, vedem ce s-a întâmplat în Austria, vedem în Suedia unde-s la guvernare, în Olanda unde-s la guvernare. A doua și a treia generație care deja scâștigă consistență găsește mai mult susținători, poate și oameni mai bine pregătiți care să-i pună în prim plan și atunci foarte greu [00:37:00] combați dacă nu ai argumente solide.Acum da, nu vreau să critic personal, dar e o realitate. Simeon nu are foarte mult continuu și atunci e foarte mai ușor de combătut din punctul ăsta de vedere. Nu George Buhnici: are Victor Negrescu: deloc. Are în plan să vândă apartamente de 30-35. Cât era? Au crescut mai nou că e inflație. Mai mult de 35. Dar trecând peste chestiunea asta, e adevărat, nu există consistență.Există radicalism. Dar hai să mai George Buhnici: rămânem o secundă la Simeon. Este el un satelit al PSD-ului? S-a comportat ca un satelit și a fost Victor Negrescu: susținut. Așa zici? Eu nu știu. O să spun ce am spus în emisiunea care mi-a adus de servicii. Dacă l-a susținut cineva, să-l dăm afară din partid. George Buhnici: Foarte direct. Au recunoscut că l-au susținut.Deci este mascotă. Oricum o să iasă cineva acum și o să ne contrazică ceea ce abia aștept. Din nou a fost o glumă. Victor Negrescu: Mi-a George Buhnici: plăcut.Victor Negrescu: Asta [00:38:00] fost meta. Eu citesc destul de mult și îmi place să mă documentez. Și dacă citești istoria social-democrației revin la ea. Când extremiști ăștia au căutat să omoare socialdemocrația structurală, eu nu aș putea nici măcar să glumesc cu privire la posibilitatea de a da un vot unor extremiști. Nu pot George Buhnici: chestiunea aceasta.Știu dar PSD-ul e în pană de idei înainte de fiecare alegeri și la doamna Dăncilă s-a întâmplat. Vin cu tot felul de chestii cu steagul, semnele la populare noi suntem populari dintr-o dată devenim foarte populari pentru că ne uităm la populiști cum cresc și nu știm cum să facem altceva. Că nu reușim să explicăm socialdemocrația că este complicată, este elitistă, habar n-am de ce, nu poate PSD-ul să o explice și atunci alunecă în popular populism Se duce în zona asta, acolo, puf se întâlnește cu ăștia.Victor Negrescu: Eu cred că e o greșeală să caut să copiezi extremismul. Pentru că, oricum, originalul o să fie tot timpul mai bun. Exact. [00:39:00] Socialdemocratii și multe partide mainstream au căutat să-i copieze pe extremiști și, de fapt doar l-au dat mai multă forță. Și trebuie să recunosc și această greșeală. Istoric, nu mă refer acum, Partidul Socialdemocrat a cultivat o bună parte din aceste idei și valori De care au profitat partidele extremiste.Fie că vorbim de perioada aceea cu Liviu Dragnea, fie că vorbim de perioada Victor Ponta, care a făcut primele slogane în această direcție și ne-am creat singur groapa. Acum ce face Partidul Social Democrat? Ca să sară în ea sau vrea să o acopere construind ceva mai serios lângă? Eu sper să fim capabili să mergem înainte să avem un proiect.Din nou nu este despre persoane, pentru că știu că lumea e cociată pe subiectul ăsta și am văzut că și tu insisti, Marcel Ciolacu, Marcel Ciolacu, nu e vorba despre el. Nu e despre Marcel Ciolacu este vorba George Buhnici: despre lipsa de educație, incompetență și lipsa de performanță. Marcel Ciolacu le [00:40:00] întrupează Și mai este și fals pe deasupra Și nici nu ne arată diplomaia de bacalaureat Am mințit cu Nordisu O să-i spun să vină în emisiune cu tine Mi-e greu să răspund în numele lui La Victor Negrescu: toate aceste întrebări Acum am George Buhnici: aflat, o să-i zic de chestiunea aceasta Dar nu-i vina ta Numai că tu ești singurul pesedist De un pic de frunte așa Care a venit Victor Negrescu: Fără întrebări înainte Trec eu prin filtru acesta Dar eu cred sincer Că trebuie să gândim Ce vrem în următorii ani Pentru zona aceasta politică Și să fim foarte atenți La deciziile luate De exemplu sunt decizii greu explicat Ultima decizie a CNA Prin care s-a dat jos conținut Poate unele Videouri trebuiau date jos Probabil că reacția ta să fie mai rapidă.Dar poate altele nu trebuiau. Pentru că nu trebuie să închizi nici dialogul. Uite mă uit la tine și nu spun pentru că este invitatul tău, [00:41:00] dar m-am uitat pe platforma asta, Twitter X, cum te lupsi pentru ideile tale. Eu n-aș vrea ca X să te dea jos, Musk, pentru că nu ai acești opinii cu Musk. Adică trebuie să fie conținutul tău rămas acolo.Dar trebuie să găsim niște soluții ca această dezbatere să fie una reală. Și aici intervine și Europa. Sau cum e, intri într-o dezbatere cu boți sau intri într-o dezbatere cu oameni care folosesc profile false. Nici asta nu mi se pare normal. Adică să poți astăzi la cât de important este social media, să ai oameni cu nume false care spun absolut orice.Eu am trecut prin experiența asta. Să fiu amenințat cu moartea, să-mi spună lumea că îmi caută familia. Am primit mesaje de genul Și cu toate astea ai venit pe jos. Te-am văzut aici. George Buhnici: Ai parcat undeva? Ai șofer? Victor Negrescu: Nu George Buhnici: am Victor Negrescu: șofer. M-am mirat că aveam loc de parcare în curte. Ai venit pe jos, ai sunat la portă. Nu m-a atacat nimeni.Nici când merg cu metrou. Mi se întâmplă deseori. Mai sunt necunoscut. E adevărat că întâlnesc destul de mulți useriști prin metrou. Mai fac poză cu mine, mai fac o glumă cât ce cauți în metrou, dar nu mai contează. Mai vin și [00:42:00] cu mașina, evident. Încerc să fiu cât se poate de normal, fără să fiu radical sau extremist în vreun fel.Și toate aceste experiențe te ajută sincer. Foarte important pentru mine. Motivul pentru care încă predau, de exemplu, este acum după acest podcast, merg la ore. Și... Faptul că interacționez cu studenții, nu fac politică niciodată în clasă, îmi permite mie să înțeleg un pic cum văd ei lucrurile, cum le percep, cum reacționează și în trafic.Dacă stai în trafic și după ce ai stat în trafic două ore, și eu în jur toți politicienii, probabil și pe mine, pentru traficul din București, sunt niște chestiuni normale. Dar dacă nu ai aceste trăiri, nu poți să înțelegi, nu poți să vii cu soluții adecvate. George Buhnici: Dezbatere este într-adevăr importantă L-am avut recent pe Valentin Jucan aici care mi-a spus că pentru ei este o provocare uriașă să modereze, că nu sunt big brother, că nu au cum să urmărească toți și că prime se sizări.Și pe bază se sizările alea pe Digital Services Act, că știi de la nivelul în europene, ei pot [00:43:00] da jos doar conținut audio-vizual care conține chestii ilegale. Trebuie să fie ceva ilegal acolo să apară în codul penal, într-o lege încălcată și doar asta pot da jos. Chistii naziste, chestii pedofile, tot felul de nenorociri deci chestii care să fie cu adevărat ilegale și penale.Dar eu cred că suntem cu toți într-o supra-reacție la ce s întâmplat la sfârșitul anului trecut. Doar că încă nu ne-am votat toate elecțiile. Uite ai un CNA hiper-reactiv probabil în momentul ăsta, dar în același timp văd niște partide care încă nu au înțeles. Deci toate astea o dată ce se va termina și cu alegerile prezențiale o să avem în cele în dormul președinte cine va fi.Poate va fi Crin Antonescu, dar n-aș băga mâna în foc. Va trebui să ne reamintim totuși ce probleme reale avem. Pentru că tot ce discutăm acum, mai mult de 90% din tot ce este în spațiu public, este irrelevant Putem fi de Victor Negrescu: acord? Da, pot fi. Pot fi de acord. Și cred că sunt multe subiecte despre care nu vorbim.Nu vorbim despre problema sărăciei. Suntem pe primele locuri în ceea ce înseamnă numărul de [00:44:00] persoane care se află sub pragul acesta normal al sărăciei adică afectat de sărăcie severă. Cum transformăm economia noastră pentru a ține pasul cu competiția globală? Ce facem după ce o să dispare fondurile europene?90% din investițiile publice din România de la aderare până în prezent s-au făcut cu banii europeni. Deci noi suntem subvenționați de Europa. Asta este realitatea. Poți să explici George Buhnici: chestia asta pentru cei care înjură Europa? Că ne suntem într-o perfuzie de fapt? Victor Negrescu: E foarte simplu. 9 din 10 proiecte care se întâmplă într-un județ sunt făcute aceste proiecte cu banii europeni.Imaginează că dispar. Acele școli modernizate, acele companii deschise cu banii europeni, că sunt spitale care nu mai au echipamente medicale și totul e făcut din banii noștri. Asta s-ar întâmpla fără Europa. Deci noi am fost ținuți vii cu banii europeni. Ne-am dezvoltat cu banii europeni, care au generat un efect multiplicator în economie chiar consistent.Și asta a fost foarte bine. Fiecare euro băgat în România conform cifrele a generat [00:45:00] alți 3 sau 5 euro, între 3 și 5 euro în funcție de domeniu. Deci extraordinar că și-am folosit și banii unii dintre noi corect și s-au dus în economie. Deci în contextul acesta, noi nu am putea să mergem înainte inclusiv fermierii români.MULȚUMIT Și agricultura românească e ținută înviată și rămâne competitivă cu aceste fonduri care vin pe zona de agricultură pentru dezvoltarea zonelor rurale, dar și prin subvenții. Noi fără subvenții, nu am face față concurenței europene. Da, putem spune că nu-i normal ca fermiere din Franța să primească subvenții mai mari decât fermiere români, deși, ușor-ușor subvențiile românești au crescut.Noi am negociat, statul român a negociat nivelul acesta al subvenților, apropo, dar, în același timp Dacă nu am fi în Uniunea Europeană sau nu ar fi Franța în Uniunea Europeană Franța ar putea să subvenționeze fermierii și probabil că ar subvenționa și mai mult pentru că au bugetul pentru a face lucrul acesta.Europa împiedică să subvenționeze mai mult fermierii, menține o cuotă maximală pentru a menține [00:46:00] concurența la nivel european. Însă fermierul francez este subvenționat din bani francezi care trec prin Comisia Europeană. Fermierul român este subvenționat din banii francezilor și germanilor. Asta nu înseamnă că trebuie să stăm cu capul plecat.Nu cred lucrul ăsta. Să înțelegem totuși că avem beneficii și trebuie să profităm de acest moment pentru a fi și noi siguri pe bugetul nostru și pe banii noștri. Noi acum suntem o familie care în fiecare zi primim bani de la rudele noastre din străinătate și la un moment dat se taie robinetul. Și tot noi ne plângem, tot noi suntem nemulțumiți, tot noi suntem supărați că de ce lucrează aia în diaspora?Apropo de ce spun unii în stânga și în dreapta. Nu! Avem nevoie de această construcție comună, însă avem nevoie în această familie și de responsabilitatea din partea noastră. Au trecut, știi, 18 ani de la aderare. Nu mai suntem un nou stat membru. Deja suntem la început de viață de adult în Europa. Și aici e important.Care e job-ul pe care le vrem? Ce vrem să facem pentru [00:47:00] familie? Cât contribuim la chirie? Care este proiectul nostru pentru familia noastră? Lucrurile astea trebuie să fie definite astăzi, nu mai târziu Pentru că dacă ajungem la 25 de ani, o să apară un nivel de frustrare. Tânărul acela care la 25 de ani este din nou în casa familiei și nu-l ascultă nimeni.Despre asta este vorba. E simplu de explicat, dar trebuie să prezentăm acest proiect. Și asta trebuie să facă viitorul președinte a României și partidele din România ca oamenii să creadă în proiectul european. Pentru că dacă nu, recent s-a publicat barometrul european. Cel mai mare nivel de încredere în Uniunea Europeană în istoria Europei 74%.Da, România... Stă bine, 7% dar este sub media europeană și nu s-a mai întâmplat asta decât să ne lădărare să fim sub media europeană. George Buhnici: Românii se uită încă nu are către vest totuși, cele mai multe curse aeriene, eu am mai zis chestia asta că urmăresc că am fost pe transporturi multă vreme, mergeam la autopei, nu prea vedeam zboruri către est, cele mai multe mers spre vest.Deci românii se uită către vest și pentru muncă și pentru vacanțe și așa mai departe și toți banii ăștia europeni, [00:48:00] făceam un calcul, deci practic în balanța asta a fondurilor europene noi suntem net câștigători ca să zic așa cu vreo 70 de miliarde dacă nu greșesc. 70 de miliarde, da. 70 de miliarde care ne-au ridicat PIB-ul de vreo 10 ori și acum suntem la vreo 350.Deci și astea în condițiile în care multe din fondurile europene sunt fraudate, sunt cheltuite anapoda, sunt investiții care nu au făcut profit, cu toate astea cu toate astea îmulțim fiecare euro de la Uniunea Europeană de vreo 3 până la 5 ori. Am vorbit inclusiv cu fermieri care mi-au spus chestia asta, că este frustrant pentru ei să vadă terenul ținut de părloagă pentru subvenție, în loc să facem mâncare și agricultură în țara asta, pentru că banii nu se verifică.Uniunea Europeană este atât de generoasă cu noi încât ne dă bani și nici nu verifică suficient Cât de mult se fraudează pentru că știe că la un moment dat românii ăia vor deveni și ei niște europeni, ajung la majorat. După 18 ani ești major acum, nu? Și începi Victor Negrescu: să-și asume rolul ăsta, să intrăm în rol.Sunt beneficiile [00:49:00] acestea financiare clare pentru România. Însă trebuie să înțelegem că nu este vorba doar despre bani. Pentru că la un moment dat o să fim în situația în care noi vom contribui mai mult la bugetul european. Și ce facem Ne plângem? Sunt atât de multe state europene care contribuie mai mult la bugetul european decât primesc.Ar fi fost foarte simplu pentru ele să plece din lumea europeană. De 18 ani francezii și George Buhnici: ăștia ne dau bani. Ne dau bani așa. Luați, faceți ceva cu ei. Știm că mai și furați, ca și cum îi dai unui copil care știe că o să-și ia și dulciuri, dar poate învață cum să-i folosească mai bine. Da, Victor Negrescu: poate merge la școală poate e mai motivat.Acum nu putem vorbi de bani gratiste. Să faci și reforme, trebuie să le spui niște standarde Să fii la un nivel european O piață deschisă concurență, competiție, da, nu este simplu Sunt și avantaje și situații mai dificile. De exemplu o mare provocare pe care am întâmplat-o este cum să facem față plecării românilor din țară.Și aici înțeleg și de ce apare această frustrare. Pentru că, mai ales [00:50:00] bătrânii care au rămas acasă se gândesc, copiii mei au plecat pentru că există Europa. Fără să-și dea seama că, de fapt, copiii lor au o șansă pentru că există Europa și poate și-au construit o familie datorită Europei. Nu-și dau seama de multe ori că drumurile care au apărut asfaltate în satele lor sau canalizarea, toate acele elemente s-au făcut cu bani europeni.Nu s-au făcut cu bani de la primărie. Da, știu că mulți primari pun chestiunea asta. Am întâlnit și eu în țară inclusiv de la Partidul Social Democrat, primari care mergeau prin sat și spuneau eu am făcut, știu lucrurile aceastea, tu ai depus dosarul. Da. Cel mult. E bine că s-a depus și dosarul. Am întâlnit și niște comunități unde nu s-a depus dosarul.La ea e acasă. Eu am primit multe provocări în politică. Cred că una dintre cele mai grele provocări în ultimii ani a fost la alegerile locale de anul trecut. Colegii mei din partid au zis Negrescu e cu Europa, exact ce spuneai tu, imagine bună, dar a să mai muncească și el. [00:51:00] Și mi-au dat să gestionez cea mai slabă organizație a PSL din punct de vedere politic, organizație în care mă regăsesc Evident fac parte din ea de mult timp dar nu m-am ocupat de politica locală.E o organizație din Alba, o organizație locală. Să nu mă ocup doar chestiuni europene, o organizație pe care o conduc PSA Activism Român. Mi-am dat o organizație județeană cu 3-4 luni înainte de alegeri Am colegi care chiar cred în socialdemocrație. Acolo dați puțin slab, cea mai puternică organizație a PNL-ului în județul respectiv.Și a trebuit să o reclădesc de la zero. De la 14% cât avea tradițional PSD în județul Alba, am luat 24%, cel mai mare număr de voturi din ultimii 30 de ani pentru PSD acolo. Și am cadus oameni noi, mulți tineri și o să spun ceva straniu. Am câștigat comunități care cât cât arată bine să erau niște proiecte făcute cu proiecte mai bune.Dar comunitățile care arătau cel mai rău, unde am pus culmea tineri [00:52:00] pregătiți oameni cu experiență, n-am reușit să le câștig. De ce? De ce Oamenii pur și simplu au zis nu vor, gata, nu vrem bani europene, nu vrem să ne amestecăm, a fost o respingere față de nou, au spus noi rămânem noi cu noi, n-are rost să vină cineva în plus.Cum s-au creat niște microclimate de convingeri de opinii bule care sunt fie fizic în anumite comunități, fie virtuale online, oameni care pur și simplu sunt convinși că trebuie să respingă orice vine din exterior, orice idee nouă că modernizarea este ceva care se face împotriva lor. Și da, trebuie să explicăm toată modernizarea asta.De exemplu acum, la nivel european am decis ca în câțiva ani permisele de conducere să fie digitalizate. Și valuă pe internet. Wow, ne fură datele! Ce scult chestiune asta! De ce mi-anulează permisul în altă țară și mi-l anulează și aici acum? Da, adică nu poți să comiți o [00:53:00] ilegalitate afară că te prinde.Păi nu trebuie să faci nimic ilegal. Despre asta e vorba. Și mai apare portofelul digital. Pe lângă pandemie, al doilea subiect important pentru extrema dreaptă în Europa a fost opoziția la crearea portofelului digital european. Adică un site Securizat, unde tu poți să-ți urci documentele, evident l-ai și în format fizic și permisul o să poți să-l în format fizic dar ți le urci acolo ca să le ai digitalizate, să nu te mai cauți prin buzunare pentru documente și ai diploma, ai permisul, ai toate chestiunile care țin de experiența ta profesională intri acolo pur și simplu cod QR, foarte ușor foarte facil.O poziție pe internet, am avut oameni care mi-au scris Negrescu ai votat în Parlamentul European să ni se fure datele. Eu nu-i blâmesc pe oamenii care mi-au scris, dar ca o să înțeleg de ce au ajuns în situația asta și cât important e să-i explicăm. Și nu e simplu sincer, nu e simplu cu persoane radicalizate să explici.O poți face individual, George Buhnici: dar [00:54:00] trebuie faci statul. Corect? Victor Negrescu: Da, sunt lucruri structurale. Adică și aici mai apare chestiunea asta. M-am întâlnit cu ministrul francez al afacelor europene, a fost și România. A venit în România să prezinte raportul pe care l-au făcut serviciile franceze cu privire la influențele străine în campania din România pentru prezidențiale.Foarte ok. George Buhnici: Aș Victor Negrescu: vrea și România, apropo să prezinte un raport. A venit cu George Buhnici: jandarmii ăia care au participat la proteste aici? N-ai auzit-o pe aia cu jandarmii Victor Negrescu: francezi? Nu erau niciun jandarm dar erau niște buni profesioniști, niște cum ea, niște doamne care au lucrat la acel raport Și prezenta tot ce se întâmplă exact Care sunt efectele și cum s-a făcut această influențare manipulare.Și nu, oamenii se uită la noi, a, politicial, ne spune că a fost manipulat, dar noi credem în [00:55:00] ceea ce facem. Da, eu chiar cred că oamenii au crezut în Georgescu, cred în continuare în aceste idei și poate nu ne dăm seama Cred că și eu am fost supus acestor influențe. Când dai scroll mai vezi niște clipuri și vezi tot timpul același clip.Nu direct, adică nu spune cineva votează Y. Când vezi la un moment dat proteste care se repetă. La un moment dat remarcasem în România, anul mă cu câțiva ani, erau video ads prin Google, promovau niște proteste Adică nu vorbim de ceva incipient și nu contează volumul financiar că a fost 500.000 de euro, că a fost un milion că au fost 4 milioane de euro băgate.Nu volumul, contează tehnica și faptul că cineva a căutat să ne inducă anumite sentimente, să ne conducă într-o direcție și asta nu este normal. Care sunt emoțiile alea Care sunt sentimentele de care [00:56:00] vorbești? Cred că dezamăgirea față de democrație și de ce s-a întâmplat în ultimii ani și aici s-a speculat...O chestie care circulă des. 35 de ani nu s-a întâmplat nimic, doar s-a furat. Și pe această chestiune s-a cultivat sentimentul că democrația e de vină și partidele sunt de vină. Deși și partidele sunt de vină, recunosc lucrul ăsta. Dar scopul a fost împotriva democrației, cultivând ideea unui lider autoritar.Cred că asta a fost centrul, au fost mult mai multe George Buhnici: Nu a cultivat liderul autoritar. Îți spun că democrația e proastă și atunci alternativa care e? Un lider? Păi Victor Negrescu: nu, arătau că erau circulele acelea cu Ceaușescu care decide și l-a arătat pe Putin cât șmecheră Putin și așa mai departe Deci au fost chestii care cultivau ideea unui lider autoritar direct.Și s-au dus aceste sentimente. Eu, de când au avut aceste alegeri prezidențiale, caut să fac întâlniri diferite cu cetățenii. Și mai nou, mai ales în alba și nu numai, îi rog pe colegii mei să ne întâlnim cu persoane care nu sunt afiliate politic pe niște caracteristici [00:57:00] comune. Și Prima întâlnire a fost cu circa 20 de tineri Grupe de vârstă diferite, unii angajați, unii la studii și unii mai tineri.Și i-am întrebat care este super puterea politică pe care ar vrea să o aibă fiecare dintre ei. Încerc să fac o discuție mai interesant. Și cei mai tineri din sală de 18 ani, mi-au zis vrem un lider autoritar să decide asta. Deci ei erau cei mai radicalizați. Unul dintre ei cântea la chitară foarte talentat, mi-a arătat și clipurile lui pe YouTube, dar un rock alternativ.Și nu m-am pus de abține și am zis, a văzut mișto ce cânt foarte tare, l pus să ne arate, chiar foarte talentat copilul. Și i-am zis, da știi muzica asta cu un lider autoritar Dar s-ar putea se spună... Că nu ai voie să cânti muzica asta, că nu este muzica aia structurală și pe vremea comuniștilor n-aveai voie să cânti sau să faci absolut [00:58:00] orice.Păi eu n-am înțeles așa. Păi da, că într-un sistem autoritar, liderul suprem decide. Dacă tu vrei asta, el îți spune ce muzică ai voie să cânti. Păi eu n-am privit așa. M-am gândit că e un lider autoritar care face curățenii. Păi ce înseamnă curățenie? Adică cred că trebuie să punem și noi întrebările de genul acesta.Ce înseamnă când scrie hashtag să facem curățenie sau ce-a folosit expresia asta extremiștii? Hai să întrebăm concret ce înseamnă. Nu au răspuns. Ce înseamnă vrem turul 2 înapoi? Ce înseamnă chestiunea asta? Adică să răstoane democrația, să nu se mai respecte nimic nicio regulă nicio decizie și așa mai departe Adică dacă intrăm în detalii Cred că extremiștii pierd dezbaterea De aceea trebuie să-i confruntăm.Clasa politică a decis să facă un pas în spate. Eu, motivul pentru care poate sunt și astăzi la tine în această dezbatere, este pentru că eu de când am avut loc ale acestei legile parlamentare, n-am avut o ezitare în a vorbi despre extremism, pericolul lor, numind Georgescu, [00:59:00] Simeon, Șoșoacă, Victor Ponta și așa mai departe N-am avut o problemă în interiorul partidului sau public.Și nu te ascund că am mai primit niște telefoane, inclusiv de la prieteni pe bune, chiar prieteni din partii sau din exterior sau de la alte partii de care mi-au zis Victor, nu vrei să o lași mai moale? Lasă-o mai moale, așa că nu e bine. Pierdem electorat. Dar ce vrei să posti tu lupta asta? Candidez la prezidențiale?Nu, dom'le nu candidez. Eu George Buhnici: cred că un PSD cu tine în frunte ar fi avut o șansă mult mai bună să iasă din blaștină asta. Și, din nou, not a big fan, da? Suntem aici doar că efectiv percepție Mă uit din afară Ca jurnalist mă uit la percepție în primul rând Lucrez cu oameni de multă vreme Mă uit la mass media Mă uit la felul în care se uită cei care îți pun ție întrebări Mă uit la felul în care se raportează oamenii la tine Tu nu ai hate Victor Negrescu: Decât George Buhnici: de la troll Victor Negrescu: Poate am și hate Se mai întâmplă Și mi-asum și oameni Care nu mă simpatizează Și e normal lucrul acesta Dar revenind la [01:00:00] chestiunea aceasta Trebuie să combatem Trebuie să fim proactiv Să fim prezenți în dezbaterea aceasta Și nu merg doar mesaje date la reuniuni de partii Adică trebuie să fii acolo La firul ierbii Să duci această luptă Cred că avem o responsabilitate liderii politici, mai inclus și pe mine prin prisma funcției acestea de vice-princip de la Parlamentul European, să-i apărăm și pe cei care sunt atacați.Eu, după ce s-a făcut în România lista celebra lui Soros pe care am fost și eu, am fost pe televiziune primul eram primul la reportajele. Te-ai întâlnit vreodată cu Soros îl știi? Două zile, nu, niciodată. Ai avut colaborări? Nu nu. Nu te-ai atins în niciun ONG de acolo? Acum nu știu câte ONG-uri au fost, dar lucrez și cu ONG-uri, sindicate, patronate.Acum m-am întâlnit cu unii care sunt de extremă dreapta, că am fost cu Victor Ponta la același partid. Deci nu e adevărat să spui George Buhnici: public chestia asta că ai sau n-ai legături directe sau

The world is completely different than it was before ChatGPT.

Alan was joined by the incomparable Melissa Obrotka, also known as "The Badass Hygienist!" They recorded this conversation live at the Chicago Midwinter Dental Meeting. The episode dives deep into Melissa's journey in dental hygiene, her passion for progressive care, and her insights on the current state and future of the profession. Melissa shares the story behind her "Badass Hygienist" nickname, stemming from her proactive approach to improving patient care and her willingness to advocate for better technology and techniques. She recounts her experience transitioning to a periodontal prosthetics practice and the steep learning curve involved in maintaining complex implant cases as well as how she discovered "Guided Biofilm Therapy" (or GBT) a techniqu that she now teaches and uses clinically. Dr. Mead and Melissa also tackle some of the challenging issues facing dentistry today, including the hygiene shortage and potential solutions, the complexities of insurance-driven care, and the need for better communication and understanding between dentists and hygienists. Melissa offers her perspective on how hygienists can move beyond "polishing a paycheck" and embrace a more therapeutic and patient-centered approach. Some links from the show: itsthebadasshygienist (Melissa's Instagram) Guided Biofilm Therapy from EMS Join the Very Dental Facebook group using the password "Timmerman," Hornbrook" or "McWethy," "Papa Randy" or "Lipscomb!" The Very Dental Podcast network is and will remain free to download. If you'd like to support the shows you love at Very Dental then show a little love to the people that support us! -- Crazy Dental has everything you need from cotton rolls to equipment and everything in between and the best prices you'll find anywhere! If you head over to verydentalpodcast.com/crazy and use coupon code “VERYDENTAL10” you'll get another 10% off your order! Go save yourself some money and support the show all at the same time! -- The Wonderist Agency is basically a one stop shop for marketing your practice and your brand. From logo redesign to a full service marketing plan, the folks at Wonderist have you covered! Go check them out at verydentalpodcast.com/wonderist! -- Enova Illumination makes the very best in loupes and headlights, including their new ergonomic angled prism loupes! They also distribute loupe mounted cameras and even the amazing line of Zumax microscopes! If you want to help out the podcast while upping your magnification and headlight game, you need to head over to verydentalpodcast.com/enova to see their whole line of products! -- CAD-Ray offers the best service on a wide variety of digital scanners, printers, mills and even  their very own browser based design software, Clinux! CAD-Ray has been a huge supporter of the Very Dental Podcast Network and I can tell you that you'll get no better service on everything digital dentistry than the folks from CAD-Ray. Go check them out at verydentalpodcast.com/CADRay!  

The above title does not do Dan Swift justice. Dan also has his own podcast, successful Youtube channel and he has released seven music albums. Talk about being unstoppable! I met Dan when I appeared as a guest on his podcast, Time We Discuss and I knew he would contribute to a fascinating story here.   Dan grew up with an interest in music. For a time he thought he wanted to write music for video games. Along the way he left that idea behind and after graduating from college he began working at designing websites. He has made that into his fulltime career.   As he grew as a website designer and later as a supervisor for a school system coordinating and creating the school sites Dan took an interest in accessibility of the web. We talk quite a bit about that during our time together. His observations are fascinating and right on where web access for persons with disabilities is concerned.   We also talk about Dan's podcast including some stories of guests and what inspires Dan from his interviews. I hope you enjoy this episode as much as I.       About the Guest:   Originally wanting to write music for video games or become an audio engineer, Dan Swift graduated from a small Liberal Arts college with a degree in Music Composition (Bachelor of Arts) and Music Recording Technology (Bachelor of Music).  Dan went on to release seven EP albums between 2003 and 2024. Most recently, "Parallels" dropped on Leap Day, 2024.  Dan has always had a passion for shaking up genres between Eps writing classical, electronic, and modern rock music.   While creating music has always been a passion, Dan took a more traditional professional path as a web developer. While on this path, Dan had a lot of experience with accessibility standards as it relates to the web and he values accessibility and equity for everyone both inside and outside the digital workspace. Having received his MBA during COVID, Dan went on to a leadership position where he continues to make a difference leading a team of tech-savvy web professionals.   In early 2024, I created a podcast and YouTube channel called "Time We Discuss" which focuses on career exploration and discovery. The channel and podcast are meant for anyone that is feeling lost professionally and unsure of what is out there for them. Dan feels that it is important for people to discover their professional passion, whatever it is that lights them up on the inside, and chase it. So many people are unfulfilled in their careers, yet it doesn't have to be this way.   When not working, Dan enjoys spending time with his wife and three kids. They are a very active family often going to various extracurricular events over the years including flag football, soccer, gymnastics, and school concerts.  Dan's wife is very active with several nonprofit organizations including those for the betterment of children and homelessness.  Dan enjoys playing the piano, listening to podcasts, and listening to music.  Dan is very naturally curious and is a slave to a train of never-ending thoughts.   Ways to connect with Dan:   Time We Discuss on YouTube Time We Discuss on Spotify Time We Discuss on Twitter/X Time We Discuss on Instagram Time We Discuss on BlueSky   Time We Discuss Website Dan Swift Music Website   About the Host:   Michael Hingson is a New York Times best-selling author, international lecturer, and Chief Vision Officer for accessiBe. Michael, blind since birth, survived the 9/11 attacks with the help of his guide dog Roselle. This story is the subject of his best-selling book, Thunder Dog.   Michael gives over 100 presentations around the world each year speaking to influential groups such as Exxon Mobile, AT&T, Federal Express, Scripps College, Rutgers University, Children's Hospital, and the American Red Cross just to name a few. He is Ambassador for the National Braille Literacy Campaign for the National Federation of the Blind and also serves as Ambassador for the American Humane Association's 2012 Hero Dog Awards.   https://michaelhingson.com https://www.facebook.com/michael.hingson.author.speaker/ https://twitter.com/mhingson https://www.youtube.com/user/mhingson https://www.linkedin.com/in/michaelhingson/   accessiBe Links https://accessibe.com/ https://www.youtube.com/c/accessiBe https://www.linkedin.com/company/accessibe/mycompany/   https://www.facebook.com/accessibe/       Thanks for listening!   Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page. Do you have some feedback or questions about this episode? Leave a comment in the section below!   Subscribe to the podcast   If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can subscribe in your favorite podcast app. You can also support our podcast through our tip jar https://tips.pinecast.com/jar/unstoppable-mindset .   Leave us an Apple Podcasts review   Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts.       Transcription Notes:   Michael Hingson ** 00:00 Access Cast and accessiBe Initiative presents Unstoppable Mindset. The podcast where inclusion, diversity and the unexpected meet. Hi, I'm Michael Hingson, Chief Vision Officer for accessiBe and the author of the number one New York Times bestselling book, Thunder dog, the story of a blind man, his guide dog and the triumph of trust. Thanks for joining me on my podcast as we explore our own blinding fears of inclusion unacceptance and our resistance to change. We will discover the idea that no matter the situation, or the people we encounter, our own fears, and prejudices often are our strongest barriers to moving forward. The unstoppable mindset podcast is sponsored by accessiBe, that's a c c e s s i capital B e. Visit www.accessibe.com to learn how you can make your website accessible for persons with disabilities. And to help make the internet fully inclusive by the year 2025. Glad you dropped by we're happy to meet you and to have you here with us.   Michael Hingson ** 01:20 Well, hi everybody. Welcome once again. Wherever you may be, to unstoppable mindset, I am your host, Mike hingson, sometimes I say Michael hingson, and people have said, Well, is it Mike or Michael? And the answer is, it doesn't really matter. It took a master's degree in physics and 10 years in sales for me to realize that if I said Mike Hingson on the phone, people kept calling me Mr. Kingston, and I couldn't figure out why, so I started saying Michael Hingson, and they got the hinckson part right, but it doesn't matter to me. So anyway, Mike hingson, or Michael hingson, glad you're with us, wherever you are, and our guest today is Dan Swift, who has his own pine podcast, and it was actually through that podcast that we met, and I told him, but I wouldn't do it with him and be on his podcast unless he would be on unstoppable mindset. And here he is. Dan is a person who writes music, he's an engineer. He does a lot of work with web design and so on, and we're going to get into all that. So Dan, I want to welcome you to unstoppable mindset. We're really glad you're here.   Dan Swift ** 02:25 Michael, it's a pleasure to be here. Thank you so much for inviting me. I am. I'm super excited.   Michael Hingson ** 02:30 Well, looking forward to getting to spend more time with you. We did yours time to discuss, and now we get this one. So it's always kind of fun. So, and Dan is in Pennsylvania, so we're talking across the continent, which is fine. It's amazing what we can do with electronics these days, telling us not like the good old days of the covered wagon. What can I say? So, So Dan, why don't you tell us a little bit about kind of the early Dan, growing up and all that.   Dan Swift ** 02:57 Oh, geez. How far   Michael Hingson ** 02:58 back to go? Oh, as far as you want to go,   Dan Swift ** 03:02 Well, okay, so I am, I am the youngest of five. Grew up just outside of Philadelphia as being the youngest. You know, there are certain perks that go along with that. I get to experience things that my parents would have previous said no to the older siblings. And you know how it is with with, you know, if you have more than one kid, technically, you get a little more relaxed as you have more but then I also had the other benefit of, you know, hearing the expression, there are young ears in the room, I will tell you later. So I kind of got some of that too. But I grew up outside of Philadelphia, had a passion for music. Pretty early on. I was never good at any sports. Tried a number of things. And when I landed on music, I thought, you know, this is this is something that I can do. I seem to have a natural talent for it. And I started, I tried playing the piano when I was maybe eight or nine years old. That didn't pan out. Moved on to the trumpet when I was nine or 10. Eventually ended up picking up guitar, bass, guitar, double bass revisited piano later in life, but that's the musical side of things. Also, when I was young, you know, I had a passion for role playing games, Dungeons and Dragons, was really big when I was a teenager, so I was super excited for that. Yeah, that's, that's kind of those, those memories kind of forced me, or kind of shaped me into the person that I am today. I'm very light hearted, very easy going, and I just try to enjoy life.   Michael Hingson ** 04:30 I played some computer games when computers came along and I started fiddling with them, the games I usually played were text based games. I've never really played Dungeons and Dragons and some of those. And I I'm sure that there are accessible versions of of some of that, but I remember playing games like adventure. You remember? Have you heard of adventure? I have, yeah. So that was, that was fun. Info con made. Well, they had Zork, which was really the same as adventure, but they. At a whole bunch of games. And those are, those are fun. And I think all of those games, I know a lot of adults would probably say kids spend too much time on some of them, but some of these games, like the the text based games, I thought really were very good at expanding one's mind, and they made you think, which is really what was important to me? Yeah, I   Dan Swift ** 05:21 completely agree with that too. Because you'd be put in these situations where, you know true, you're trying to solve some kind of puzzle, and you're trying to think, Okay, well, that didn't work, or that didn't work, and you try all these different things, then you decide to leave and come back to and you realize later, like you didn't have something that you needed to progress forward, or something like that. But, but it really gets the brain going, trying to create with these, uh, come up with these creative solutions to progress the game forward. Yeah, which   Michael Hingson ** 05:43 and the creative people who made them in the first place? What did they? Yeah, they, I don't know where they, where they spent their whole time that they had nothing to do but to create these games. But hey, it worked. It sure. Did you know you do it well. So you went off to college. Where'd you go? Sure,   Dan Swift ** 06:02 I went to a small liberal arts college, Lebanon Valley College in Pennsylvania. It's near, it's near Hershey. It was, it was weird in that my the entire school was about half the size of my entire high school. So that was very, very weird. And then you talk to these other people. And it's like, my high school was, you know, very large by comparison. But for me, it was like, well, high school, that's what I knew. But yeah, it was I went to, I went to 11 Valley College near Hershey. I studied, I was a double major. I studied music composition and music recording,   Michael Hingson ** 06:35 okay, and, oh, I've got to go back and ask before we continue that. So what were some of the real perks you got as a kid that your your older siblings didn't get?   Dan Swift ** 06:45 Oh, geez, okay. I mean,   Michael Hingson ** 06:49 couldn't resist, yeah, probably, probably   Dan Swift ** 06:51 some of the more cliche things. I probably got to spend the night at a friend's house earlier than my oldest brother. For instance, I know my parents were a little more concerned about finances. So I know my oldest brother didn't get a chance to go away to college. He did community college instead. And then, kind of, my sister was a very similar thing. And then once we got, like, about halfway down, you know, me and my two other brothers, we all had the opportunity to go away to college. So I think that was, that was definitely one of the perks. If I was the oldest, I was the oldest, I probably wouldn't have had that opportunity with my family. Got   Michael Hingson ** 07:24 it well, so you went off and you got a matt a bachelor's in music, composition and music recording. So that brought you to what you were interested in, part, which was the engineering aspect of it. But that certainly gave you a pretty well rounded education. Why those two why composition and recording? Sure.   Dan Swift ** 07:43 So if we talk about the music first at that time, so this is like the the late 90s, early 2000s any kind of digital music that was out there really was, was MIDI based, and anyone that was around that time and paying attention, it was like these very like, like that music kind of sound to it. So there wasn't a whole lot going on with MIDI. I'm sorry, with music as far as how great it sounded, or I shouldn't say, how great it sounded, the the instruments that are triggered by MIDI, they didn't sound all that great. But around that time, there was this game that came out, Final Fantasy seven, and I remember hearing the music for that, and it was all, it was all electronic, and it was just blown away by how fantastic it sounded. And And around that time, I thought, you know, it'd be really cool to get into writing music for video games. And that was something I really kind of toyed with. So that was kind of in the back of my head. But also, at the time, I was in a band, like a rock band, and I thought, you know, I'm going to school. They have this opportunity to work as a music engineer, which is something I really wanted to do at the time. And I thought, free studio time. My band will be here. This will be awesome. And it wasn't until I got there that I discovered that they also had the music composition program. It was a I was only there maybe a week or two, and once I discovered that, I was like, Well, this is gonna be great, you know, I'll learn to write. Know, I'll learn to write music. I can write for video games. I'll get engineering to go with it. This is gonna be fantastic. Speaking   Michael Hingson ** 09:07 of electronic music, did you ever see a science fiction movie called The Forbidden Planet? I did not. Oh, it's music. It's, it's not really music in the sense of what what we call, but it's all electronic. You gotta, you gotta find it. I'm sure you can find it somewhere. It's called the Forbidden Planet. Walter pigeon is in it. But the music and the sounds fit the movie, although it's all electronic, and electronic sounding pretty interesting.   Dan Swift ** 09:37 Now, is that from, I know, like in the 50s, 60s, there was a lot of experiments. Okay, yeah,   Michael Hingson ** 09:45 yeah, and, but again, it fit the movie, which was the important part. So it certainly wasn't music like John Williams today and and in the 80s and all that. But again, for the movie, it fit. Very well, which is kind of cool. Yeah,   Dan Swift ** 10:02 I'll definitely have to check that out. I remember when I was in school, we talked about like that, that avant garde kind of style of the the 50s, 60s. And there was a lot of weird stuff going on with electronics, electronic music. Um, so I'm very curious to see, uh, to check this out, yeah, yeah.   Michael Hingson ** 10:14 You have to let me know what, what you find, what you think about it, when you get to chance to watch it, absolutely or actually, I I may have a copy. If I do, I'll put it in a dropbox folder and send you a link. Fantastic. So you graduated. Now, when did you graduate?   Dan Swift ** 10:32 Sure, so I graduated in 2003 okay,   Michael Hingson ** 10:35 so you graduated, and then what did you do? So,   Dan Swift ** 10:41 backing up about maybe 612, months prior to that, I decided I did not want to be a I didn't want to write music for video games. I also did not want to work in a recording studio. And the reason for this was for music. It was, I didn't it was, it was something I really, really enjoyed, and I didn't want to be put in a position where I had to produce music on demand. I didn't want to I didn't want to do that. I didn't want to lose my hobby, lose my passion in that way. So I decided that was out. And then also, when it came to working in a studio, if I wanted to be the engineer that I really wanted to be, I would have to be in a place where the music scene was really happening. So I'd have to be in like Philadelphia or Los Angeles or Nashville or deep in Philly or something like that. And I do not like the cities. I don't feel comfortable in the city. So I was like, that's not really for me either. I could work in like a suburb studio. But I was like, not, not for me. I don't, not for me. So when I graduated college, I ended up doing freelance web work. I had met through, through a mutual friend I was I was introduced to by a mutual friend, to a person that was looking for a new web designer, developer. They lost their person, and they were looking for someone to take over with that. And at the time, I did a little bit of experience doing that, from when I was in high school, kind of picked it up on the side, just kind of like as a hobby. But I was like, Ah, I'll give this a shot. So I started actually doing that freelance for a number of years after graduation. I also worked other jobs that was, like, kind of like nowhere, like dead end kind of jobs. I did customer service work for a little bit. I was a teacher with the American Cross for a little bit, a little bit of this and that, just trying to find my way. But at the same time, I was doing freelance stuff, and nothing related to music and nothing related to technology,   Michael Hingson ** 12:29 well, so you learned HTML coding and all that other stuff that goes along with all that. I gather, I   Dan Swift ** 12:35 sure did, I sure didn't. At the time, CSS was just kind of popular, yeah, so that. And then I learned, I learned JavaScript a little bit. And, you know, I had a very healthy attitude when it when it came to accepting new clients and projects, I always tried to learn something new. Anytime someone gave me a new a new request came in, it was like, Okay, well, I already know how to do this by doing it this way. But how can I make this better? And that was really the way that I really propelled myself forward in the in the digital, I should say, when it comes to development or design.   Michael Hingson ** 13:05 Okay, so you ended up really seriously going into website development and so on.   Dan Swift ** 13:15 I did. So I continued doing freelance. And then about five years after I graduated, I started working as an audio visual technician, and also was doing computer tech stuff as part of the role as well. And while I was there, I ended up developing some web applications for myself to use that I could use to interact with our like projectors and stuff like that. Because they were on, they were all in the network, so I could interact with them using my wait for it, iPod Touch, there you go. So that was, you know, I kind of like started to blend those two together. I was really interested in the web at the time, you know, because I was still doing the freelance, I really wanted to move forward and kind of find a full time position doing that. So I ended up pursuing that more and just trying to refine those skills. And it wasn't until about about five years later, I ended up working as a full time web developer, and then kind of moved forward from   Michael Hingson ** 14:09 there, iPod Touch, what memories? And there are probably bunches of people who don't even know what that is today. That   Dan Swift ** 14:16 is so true, and at the time that was cutting edge technology,   Michael Hingson ** 14:21 yeah, it was not accessible. So I didn't get to own one, because was later than that that Steve Jobs was finally kind of pushed with the threat of a lawsuit into making things accessible. And then they did make the iPhone, the iPod, the Mac and so on, and iTunes U and other things like that, accessible. And of course, what Steve Jobs did, what Apple did, which is what Microsoft eventually sort of has done as well, but he built accessibility into the operating system. So anybody who has an Apple device today. Troy actually has a device that can be made accessible by simply turning on the accessibility mode. Of course, if you're going to turn it on, you better learn how to use it, because the gestures are different. But it took a while, but, but that did happen. But by that time, I, you know, I had other things going on, and so I never did get an iPod and and wasn't able to make it work, but that's okay. But it's like the CD has gone away and the iPod has gone away, and so many things and DVDs have gone away.   Dan Swift ** 15:31 Yes, so true. So true. You know, just as soon as we start to get used to them   Michael Hingson ** 15:35 gone. I think there is, well, maybe it's close. There was a blockbuster open up in Oregon. But again, Blockbuster Video, another one, and I think somebody's trying to bring them back, but I do see that vinyl records are still being sold in various places by various people. Michael Buble just put out a new album, The Best of Buble, and it's available, among other things, in vinyl. So the old turntables, the old record players, and you can actually buy his album as a record and play it, which is kind of cool. Yeah, they've been   Dan Swift ** 16:07 very big with marketing, too. It's been kind of a marketing, I don't want to say gimmick, but in that realm, you kind of like, hey, you know, this is also available in vinyl, and you try to get the people that are like the audio files to really check it out. I never really took the vinyl personally, but I know plenty of people that have sworn by it. Well,   Michael Hingson ** 16:25 I've heard a number of people say that the audio actually is better on vinyl than typical MP three or other similar file formats. Yep,   Dan Swift ** 16:35 yep. I had a friend growing up, and actually, I shouldn't say growing up, so I was already, like, in college or post college, but a buddy of mine, Craig, he was all about vinyl, and he had, he had the nice, the amplifier, and the nice, I think even, like, a certain kind of needle that you would get for the record player. And you know, you'd have to sit in the sweet spot to really enjoy it, and and I respect that, but um, for me, it was like, I didn't, I didn't hear that much of a difference between a CD and vinyl. Um, not very. Didn't have the opportunity to AB test them. But now I will say comparing a CD to like an mp three file, for instance, even a high quality mp three file, I can tell the difference on that Sure. I would never, you know, I'd use the MP threes for convenience. But if I were to have it my way, man, I'd have the uncompressed audio, no doubt about it, yeah,   Michael Hingson ** 17:27 wave forms, yep, yep, yeah. Obviously that's that's going to give you the real quality. Of course, it takes a lot more memory, but nevertheless, if you've got the space it, it really makes a lot of sense to do because mp three isn't going to be nearly as high a level quality.   Dan Swift ** 17:43 Absolutely, absolutely true. And that the way I rationalize it to myself. It's like, well, if I'm going to be though in the car or probably walking around and listening to music, I'm going to be getting all kinds of sounds from outside. Anyway, it kind of offsets the poor quality of the MP justify it.   Michael Hingson ** 17:56 That's true. Well, you know when and mp three is convenient if you want to put a bunch of stuff in a well on a memory card and be able to play it all, because if you have uncompressed audio, it does take a lot more space, and you can't put as much on a card, or you got to get a much bigger card. And now we're getting pretty good sized memory cards. But still, the reality is that that for most purposes, not all mp three will suffice.   Dan Swift ** 18:26 That is true. That is true. And I think too, you have a that the next battle is going to be mp three or a streaming,   Michael Hingson ** 18:33 yeah, yeah, that's going to be fun, isn't it? Yeah? Boy. What a world well. So one of the things I noticed in reading your bio and so on is that you got involved to a great degree in dealing with accessibility on the web. Tell me about that.   Dan Swift ** 18:55 Absolutely. Michael, so I've very strong opinions of accessibility. And this really comes back to, you know, I was, I was at my job, and I was only there as a full time developer. I wasn't there all that long, maybe a year, maybe two, and my supervisor came over to me and she said, you know, we want to start to make things more accessible. And this is like, this is like, 1012, years ago at this point, and I was like, okay, you know, and I did my little bit of research, and there wasn't a whole lot going on at the time. I don't think WCAG was a thing back then. It may have been. I can't remember if 508 was a thing at the in the Bible. It was okay, yeah. So I was doing my research, and, you know, you learn about the alt tags, and it's like, okay, well, we're doing that, okay. Then you learn about forms, and it's like, okay, well, they need to have labels, okay, but, but the turning point was this, Michael, we had a person on staff that was blind, and I was put in touch with this person, and I asked them to review like, different, different web applications. Applications we made, or forms or web pages. And the one day, I can't remember if he volunteered or if I asked, but essentially the request was, can this person come into our physical space and review stuff for us in person? And that experience was life changing for me, just watching him navigate our different web pages or web applications or forms, and seeing how he could go through it, see what was a problem, what was not a problem, was just an incredible experience. And I said this before, when given the opportunity to talk about this, I say to other developers and designers, if you ever have even the slightest opportunity to interact with someone, if they if, if you meet someone and they are using, let me, let me rephrase that, if you have the opportunity to watch someone that is blind using a navigate through the web, take, take that opportunity. Is just an amazing, amazing experience, and you draw so much from it. As a developer or designer, so very strong opinions about it, I'm all about inclusivity and making things equal for everyone on the web, and that was just my introductory experience about a dozen years ago.   Michael Hingson ** 21:07 And so what have you done with it all since? Sure, so   Dan Swift ** 21:11 with our website, we went from having about a million success criterion failures, and we've gotten it all the way down to, I think my last check, I think was maybe about 10,000 so it was huge, huge change. It's hard to get everything as because as content changes and newspaper, as new pages come online, it's hard to keep everything 100% accessible, but we know what to look for. You know, we're looking for the right contrast. We're looking for, you know, the all tags. We're looking for hierarchy with the headers. We're making sure our forms are accessible. We're making sure there aren't any keyboard traps, you know, things that most people, most web visitors, don't even think about, you know, or developers even thinking about, until you know, you need to think about them   Michael Hingson ** 22:00 well and other things as well, such as with other kinds of disabilities. If you're a person with epilepsy, for example, you don't want to go to a website and find blinking elements, or at least, you need to have a way to turn them off, yeah.   Dan Swift ** 22:13 Or or audio that starts automatically, or videos that start automatically, yeah, yeah.   Michael Hingson ** 22:19 So many different things, or video that starts automatically, and there's music, but there's no audio, so you so a blind person doesn't even know what the video is, yes, which, which happens all too often. But the the reality is that with the Americans with Disabilities Act, it's it's been interesting, because some lawyers have tried to fight the courts and say, well, but the ADA came out long before the internet, so we didn't know anything about the internet, so it doesn't apply. And finally, the Department of Justice is taking some stands to say, yes, it does, because the internet is a place of business, but it's going to have to be codified, I think, to really bring it home. But some courts have sided with that argument and said, Well, yeah, the ADA is too old, so it doesn't, doesn't matter. And so we still see so many challenges with the whole idea of access. And people listening to this podcast know that, among other things I work with a company called accessibe. Are you familiar with them? I am, Yep, yeah, and, and so that's been an interesting challenge. But what makes access to be interesting is that, because it has an artificial intelligent widget that can monitor a website, and at the at the low end of of costs. It's like $490 a year. And it may not pick up everything that a body needs, but it will, will do a lot. And going back to what you said earlier, as websites change, as they evolve, because people are doing things on their website, which they should be doing, if you've got a static website, you never do anything with it. That's not going to do you very much good. But if it's changing constantly, the widget, at least, can look at it and make a lot of the changes to keep the website accessible. The other part of it is that it can tell you what it can't do, which is cool,   Dan Swift ** 24:16 yeah, that's a really good point. You know, there's a lot of tools that are out there. They do monitor the stuff for you, you know, like we on our on our site, we have something that runs every night and it gives us a report every day. But then there are things that it doesn't always check, or it might, it might get a false positive, because it sees that like, you know, this element has a particular color background and the text is a particular color as well. But there's, you know, maybe a gradient image that lies between them, or an image that lies between them. So it's actually okay, even though the tool says it's not, or something like that. So, yeah, those automated tools, but you gotta also look at it. You know, a human has to look at those as well.   Michael Hingson ** 24:52 Yeah, it's a challenge. But the thing that I think is important with, well, say, use accessibe. An example is that I think every web developer should use accessibe. And the reason I think that is not that accessibe will necessarily do a perfect job with with the access widget, but what it will do is give you something that is constantly monitored, and even if it only makes about 50% of the website more usable because there are complex graphics and other things that it can't do, the reality is, why work harder than you have to, and if accessibility can do a lot of the work for you without you having to do it, it doesn't mean that you need to charge less or you need to do things any different, other than the fact that you save a lot of time on doing part of it because the widget does it for you. Absolutely, absolutely.   Dan Swift ** 25:47 That's that's a really, really good point too, having that tool, that tool in your tool belt, you know, yeah,   Michael Hingson ** 25:55 yeah. And it makes a lot of sense to do. And there are, there are people who complain about products like accessibe, saying artificial intelligence can't do it. It's too new. You gotta start somewhere. And the reality is that accessibe, in of itself, does a lot, and it really makes websites a lot better than they otherwise were. And some people say, Well, we've gone to websites and accessibe doesn't really seem to make a difference on the site. Maybe not. But even if your website is pretty good up front and you use accessibe, it's that time that you change something that you don't notice and suddenly accessibe fixes it. That makes it better. It's an interesting discussion all the way around, but to to deny the reality of what an AI oriented system can do is, is really just putting your head in the sand and not really being realistic about life as we go forward. I think that is   Dan Swift ** 26:52 so true. That is so true, and there's so many implications with AI and where it's going to go and what it will be able to do. You know, it's just in its infancy, and the amount of things that that the possibilities of what the future is going to be like, but they're just going to be very, very interesting.   Michael Hingson ** 27:05 I interviewed someone, well, I can't say interview, because it's conversation. Well, I had a conversation with someone earlier on, unstoppable mindset, and he said something very interesting. He's a coach, and specifically, he does a lot of work with AI, and he had one customer that he really encouraged to start using chat GPT. And what this customer did, he called his senior staff into a meeting one day, and he said, Okay, I want you to take the rest of the day and just work with chat, G, P, T, and create ideas that will enhance our business, and then let's get together tomorrow to discuss them. And he did that because he wanted people to realize the value already that exists using some of this technology. Well, these people came back with incredible ideas because they took the time to focus on them, and again, they interacted with chat, GPT. So it was a symbiotic, is probably the wrong word, but synergistic, kind of relationship, where they and the AI system worked together and created, apparently, what became really clever ideas that enhanced this customer's business. And the guy, when he first started working with this coach, was totally down on AI, but after that day of interaction with his staff, he recognized the value of it. And I think the really important key of AI is AI will not replace anyone. And that's what this gentleman said to me. He said, AI won't do it. People may replace other people, which really means they're not using AI properly, because if they were, when they find that they can use artificial intelligence to do the job that someone else is doing, you don't get rid of that person. You find something else for them to do. And the conversation that we had was about truck drivers who are involved in transporting freight from one place to another. If you get to the point where you have an autonomous vehicle, who can really do that, you still keep a driver behind the wheel, but that driver is now doing other things for the company, while the AI system does the driving, once it gets dependable enough to do that. So he said, there's no reason for AI to eliminate, and it won't. It's people that do it eliminate any job at all, which I think is a very clever and appropriate response. And I completely agree   Dan Swift ** 29:29 with that, you know, you think of other other technologies that are out there and how it disrupted, disrupted different industries. And the one example I like to use is the traffic light, you know. And I wonder, and I have no way of knowing this. I haven't researched this at all, but I wonder if there was any kind of pushback when they started putting in traffic lights. Because at that point in time, maybe you didn't have people directing traffic or something like that. Or maybe that was the event of the stop sign, it took it took away the jobs of people that were directing traffic or something like that. Maybe there was some kind of uproar over that. Maybe not, I don't know, but I like to think that things like that, you know. It disrupts the industry. But then people move on, and there are other other opportunities for them, and it progresses. It makes society progress forward.   Michael Hingson ** 30:06 And one would note that we still do use school crossing guards at a lot of schools.   Dan Swift ** 30:11 That is so true, that is true. Yeah, yeah. And especially, too, like talking about idea generation. I was talking to ginger. I forgot her last name, but she's the the president of pinstripe marketing, and she was saying that her team sometimes does the same thing that they they use chat GBT for idea generation. And I think, let's say Ashley, I think Ashley Mason, I think was her name, from Dasha social. The same thing they use, they use a chat GPT for idea generation, not not necessarily for creating the content, but for idea generation and the ideas it comes up with. It could be it can save you a lot of time. Well,   Michael Hingson ** 30:48 it can. And you know, I've heard over the last year plus how a lot of school teachers are very concerned that kids will just go off and get chat GPT to write their papers. And every time I started hearing that, I made the comment, why not let it do that? You're not thinking about it in the right way. If a kid goes off and just uses chat GPT to write their paper, they do that and they turn it into you. The question is, then, what are you as the teacher, going to do? And I submit that what the teachers ought to do is, when they assign a paper and the class all turns in their papers, then what you do is you take one period, and you give each student a minute to come up and defend without having the paper in front of them their paper. You'll find out very quickly who knows what. And it's, I think it's a potentially great teaching tool that   Dan Swift ** 31:48 is fascinating, that perspective is awesome. I love that.   Speaker 1 ** 31:52 Well, it makes sense. It   Dan Swift ** 31:55 certainly does. It certainly does. And that made me think of this too. You know, there's a lot of pushback from from artists about how that, you know, their their art was being used, or art is being used by AI to generate, you know, new art, essentially. And and musicians are saying the same thing that they're taking our stuff, it's getting fed into chat, GPT or whatever, and they're using it to train these different models. And I read this, this article. I don't even know where it was, but it's probably a couple months ago at this point. And the person made this comparison, and the person said, you know, it's really no different than a person learning how to paint in school by studying other people's art. You know, it's the same idea. It's just at a much, much much accelerated pace. And I thought, you know what that's that's kind of interesting. It's an interesting   Michael Hingson ** 32:45 perspective. It is. I do agree that we need to be concerned, that the human element is important. And there are a lot of things that people are are doing already to misuse some of this, this AI stuff, these AI tools, but we already have the dark web. We've had that for a while, too. I've never been to the dark web. I don't know how to get to it. That's fine. I don't need to go to the dark web. Besides that, I'll bet it's not accessible anyway. But the we've had the dark web, and people have accepted the fact that it's there, and there are people who monitor it and and all that. But the reality is, people are going to misuse things. They're going to be people who will misuse and, yeah, we have to be clever enough to try to ferret that out. But the fact of the matter is, AI offers so much already. One of the things that I heard, oh, gosh, I don't whether it was this year or late last year, was that, using artificial intelligence, Pfizer and other organizations actually created in only a couple of days? Or moderna, I guess, is the other one, the COVID vaccines that we have. If people had to do it alone, it would have taken them years that that we didn't have. And the reality is that using artificial intelligence, it was only a few days, and they had the beginnings of those solutions because they they created a really neat application and put the system to work. Why wouldn't we want to do that?   Dan Swift ** 34:23 I completely agree. I completely agree. And that's, again, that's how you move society forward. You know, it's similar to the idea of, you know, testing medicine on or testing medications on animals. For instance, you know, I love animals. You know, I love dogs, bunnies. I mean, the whole, the whole gamut, you know, love animals, but I understand the importance of, you know, well, do we test on them, or do we press on people, you know, you gotta, or do you not test? Or do just not you like you gotta. You gotta weigh out the pros and cons. And they're, they're definitely, definitely those with AI as well.   Michael Hingson ** 34:56 Well, I agree, and I. With animals and people. Now, I mean, as far as I'm concerned, we ought to be doing tests on politicians. You know, they're not people. Anyway. So I think when you decide to become a politician, you take a special pill that nobody seems to be able to prove, but they take dumb pills, so they're all there. But anyway, I'm with Mark Twain. Congress is at Grand Ole benevolent asylum for the helpless. So I'm an equal opportunity abuser, which is why we don't do politics on unstoppable mindset. We can have a lot of fun with it, I'm sure, but we sure could. It would be great talk about artificial intelligence. You got politicians. But the reality is that it's, it's really something that that brings so much opportunity, and I'm and it's going to continue to do that, and every day, as we see advances in what AI is doing, we will continue to see advances and what is open for us to be able to utilize it to accomplish, which is cool. I   Dan Swift ** 36:04 completely agree. Completely agree. Yeah,   Michael Hingson ** 36:06 so it'll be fun to see you know kind of how it goes. So are you, do you work for a company now that makes websites? Or what is your company that you work for? Do, sure.   Dan Swift ** 36:16 So I'm still in the education space, so I'm still, I'm like, in a state school managing a team of web professionals.   Michael Hingson ** 36:23 Okay, well, that's cool. So you keep the school sites and all the things that go along with it up at all that   Dan Swift ** 36:31 is correct. And we have lots of fun challenges when we start to integrate with third parties and got to make sure they're accessible too. And sometimes there's dialog that goes back and forth that people aren't happy with but, but it's my job to make sure, that's one of the things that we make sure happens, especially since I'm sure you've been following this. There's the Department of Justice ruling back in April, but I think it's anyone that's receiving state funding, they have to be. They have to follow the WCAG. Two point, I think, 2.1 double A compliance by April of 26 if you are a certain size, and my my institution, falls into that category. So we need to make sure that we were on the right path   Michael Hingson ** 37:06 well. And the reality is that has been around since 2010 but it took the the DOJ 12 years to finally come up with rules and regulations to implement section 508. Yep, but it's it's high time they did and they do need to do it for the rest of the internet, and that's coming, but people are just being slow. And for me personally, I think it's just amazing that it's taking so long. It's not like you have to redesign a box, that you have to go off and retool hardware. This is all code. Why should it be that difficult to do? But people throw roadblocks in your way, and so it becomes tough. Yeah, it's   Dan Swift ** 37:47 interesting, too. I remember reading this article, oh, gosh, this is probably, this is probably about a dozen years ago, and it said that, you know, the original web was 100% accessible, that it was just, you know, just text on a page pretty much. And you could do very, very simple layouts, you know, and then it got more convoluted. People would start doing tables for layouts, and tables within tables within tables, and so on and so forth. Like the original web it was, it was completely accessible. And now with, with all the the interactions we do with with client side scripting and everything like that, is just, it's a mess. If   Michael Hingson ** 38:19 you really want to hear an interesting thing, I like to look and I've done it for a long time, long before accessibe. I like to explore different sites and see how accessible they are. And one day I visited nsa.gov, the National Security Agency, which, of course, doesn't really exist. So I could tell you stories, but I went to nsa.gov, and I found that that was the most accessible website I had ever encountered. If you arrow down to a picture, for example, when you arrowed into it, suddenly you got on your screen reader a complete verbal description of what the picture was, and everything about that site was totally usable and totally accessible. I'd never seen a website that was so good contrast that with and it's changed. I want to be upfront about it, Martha Stewart Living. The first time I went to that website because I was selling products that Martha Stewart was interested. So I went to look at the website. It was totally inaccessible. The screen reader wouldn't talk at all. Now, I've been to Martha Stewart since, and it's and it's much more accessible, but, but I was just amazed@nsa.gov was so accessible. It was amazing, which I thought was really pretty cool. Of all places. You   Dan Swift ** 39:41 know, it's interesting. Before I started my my YouTube channel and podcast, I actually thought about creating a channel and or podcast about websites that are inaccessible, and I thought about calling companies out. And the more I thought about it, I was like, I don't know if I want to make that many people angry. I don't know if that's a   Michael Hingson ** 39:58 good idea. I'm. Would suggest going the other way, and maybe, you know, maybe we can work together on it. But I would rather feature websites that are accessible and tell the story of how they got there, how their people got there. I would think that would be, I hear what you're saying about making people angry. So I would think, rather than doing that, feature the places that are and why they are and and their stories, and that might help motivate more people to make their websites accessible. What do you think about that as an idea?   Dan Swift ** 40:28 I actually thought about that as well, and I was going backwards between that and and the other the negative side, because I thought, you know, bring that to light. Might actually force them to like by shedding light on it, might force them to make their site more accessible, whether what or not or not, no, but I definitely thought about those two sites.   Michael Hingson ** 40:45 Yeah, it's, it's, it's a challenge all the way around. Well, what was the very first thing you did, the first experience that you ever had dealing with accessibility that got you started down that road.   Dan Swift ** 40:58 I think it was like I said, when I work with that, that blind person, when I, when I first had that opportunity to see how he used the different web applications, we had the different web pages, and he was using a Mac. So he was using VoiceOver, he was using the, I think it's called the rotor menu, or roto something like that. Yeah, yep. So then after that happened, it was like, whoa. I need to get them back so I can, like, learn to use this as well and do my own testing. So the IT department had an old I asked them. I said, Hey guys, do you have any any old MacBooks that I can use? I was like, it can be old. I just need to test it. I need to, I need it to test for accessibility on the web. They hooked me up with an old machine, you know, it wasn't super old, you know, but it was. It worked for me. It gave me an opportunity to do my testing, and then I kind of became like the person in the department to do that. Everyone else, they didn't have the interest as much as I did. They recognized the importance of it, but they, they didn't have the same fire on the inside that I had, so I kind of took that on, and then like that. Now that I'm in the position of leadership, now it's more of a delegating that and making sure it still gets done. But I'm kind of like the resident expert in our in our area, so I'm still kind of the person that dives in a little bit by trying to make my team aware and do the things they need to do to make sure we're continuing, continuing to create accessible projects. You   Michael Hingson ** 42:20 mentioned earlier about the whole idea of third party products and so on and and dealing with them. What do you do? And how do you deal with a company? Let's say you you need to use somebody else's product and some of the things that the school system has to do, and you find they're not accessible. What do you do?   Dan Swift ** 42:42 So a lot of times, what will happen, I shouldn't say a lot of times. It's not uncommon for a department to make a purchase from a third party, and this is strictly, I'm talking in the web space. They might, they might make a purchase with a third party, and then they want us to integrate it. And this is a great example I had. It was actually in the spring the this, they had essentially a widget that would be on the on their particular set of pages, and there was a pop up that would appear. And don't get me started on pop ups, because I got very strong opinion about those. Me too, like I said, growing up, you know, late 90s, early 2000s very, very strong opinions about pop ups. So, but, but I encountered this, and it wasn't accessible. And I'm glad that in the position I'm in, I could say this unit, you need to talk to the company, and they need to fix this, or I'm taking it down. And I'm glad that I had the backing from, you know, from leadership, essentially, that I could do, I can make that claim and then do that, and the company ended up fixing it. So that was good. Another example was another department was getting ready to buy something. Actually, no, they had already purchased it, but they hadn't implemented it yet. The first example that was already implemented, that was I discovered that after the fact. So in the second example, they were getting ready to implement it, and they showed us another school that used it also a pop up. And I looked at it on the on the other school site, and I said, this isn't accessible. We cannot use this. No. And they said, Well, yes, it is. And I said, No, it isn't. And I explained to them, and I showed them how it was not accessible, and they ended up taking it back to their developers. Apparently there was a bug that they then fixed and they made it accessible, and then we could implement it. So it's nice that like that. I have the support from from leadership, that if there is something that is inaccessible, I have the power to kind of wheel my fist and take that down, take it off of our site. Do   Michael Hingson ** 44:31 you ever find that when some of this comes up within the school system, that departments push back, or have they caught on and recognize the value of accessibility, so they'll be supportive.   Dan Swift ** 44:45 I think the frustration with them becomes more of we bought this tool. We wish we had known this was an issue before we bought I think it's more of a like like that. We just wasted our time and money, possibly. But generally speaking, they do see the. Value of it, and they've recognized the importance of it. It's just more of a when others, there's more hoops everyone has to go through.   Michael Hingson ** 45:05 Yeah, and as you mentioned with pop ups, especially, it's a real challenge, because you could be on a website, and a lot of times A pop up will come up and it messes up the website for people with screen readers and so on. And part of the problem is we don't even always find the place to close or take down the pop up, which is really very frustrating   Dan Swift ** 45:30 Exactly, exactly the tab index could be off, or you could still be on the page somewhere, and it doesn't allow you to get into it and remove it, or, yeah, and extra bonus points if they also have an audio playing or a video playing inside of that.   Michael Hingson ** 45:44 Yeah, it really does make life a big challenge, which is very, very frustrating all the way around. Yeah, pop ups are definitely a big pain in the butt, and I know with accessibility, we're we're all very concerned about that, but still, pop ups do occur. And the neat thing about a product like accessibe, and one of the reasons I really support it, is it's scalable, and that is that as the people who develop the product at accessibe improve it, those improvements filter down to everybody using the widget, which is really cool, and that's important, because with individual websites where somebody has to code it in and keep monitoring it, as you pointed out, the problem is, if that's all you have, then you've got to keep paying people to to monitor everything, to make sure everything stays accessible and coded properly, whereas there are ways to be able to take advantage of something like accessibe, where what you're able to do is let it, monitor it, and as accessibe learns, and I've got some great examples where people contacted me because they had things like a shopping cart on a website that didn't work, but when accessibe fixed it, because it turns out there was something that needed to be addressed that got fixed for anybody using the product. Which is really cool.   Dan Swift ** 47:07 Yeah, that's really neat. I definitely appreciate things like that where, you know, you essentially fix something for one person, it's fixed for everyone, or a new feature gets added for someone, or, you know, a group of people, for instance, and then everyone is able to benefit from that. That's really, really awesome. I love that type of stuff.   Michael Hingson ** 47:22 Yeah, I think it's really so cool. How has all this business with accessibility and so on affected you in terms of your YouTube channel and podcasting and so on? How do you bring that into the process? That's that's   Dan Swift ** 47:37 really, really good question. I am very proud to say that I take the time to create transcripts of all my recordings, and then I go through them, and I check them for for accuracy, to make sure that things aren't correct, things are incorrect. Make sure things are correct, that they are not incorrect. So I'll make sure that those are there when the when the videos go live, those are available. Spotify creates them automatically for you. I don't know that you that I have the ability to modify them. I'm assuming I probably do, but honestly, I haven't checked into that. But so that's that's all accessible. When it comes to my web page, I make sure that all my images have the appropriate, you know, alt tags associated with them, that the the descriptions are there so people understand what the pictures are. I don't have a whole lot of pictures. Usually it's just the thumbnail for the videos, so just indicating what it is. And then I just try to be, you know, kind of, kind of text heavy. I try to make sure that my, you know, my links are not, you know, click here, learn more stuff like that. I make sure or they're not actual web addresses. I try to make sure that they're actual actionable. So when someone's using a screen reader and they go over a link, it actually is meaningful. And color contrast is another big one. I try to make sure my color contrast is meeting the appropriate level for WCAG, 2.1 double A which I can't remember what actual contrast is, but there's a contrast checker for it, which is really, really helpful   Michael Hingson ** 49:00 well. And the other, the other part about it is when somebody goes to your website again, of course, accessibility is different for different people, so when you're dealing with things like contrast or whatever, do people who come to the website have the ability to monitor or not monitor, but modify some of those settings so that they get maybe a higher contrast or change colors. Or do they have that ability?   Dan Swift ** 49:28 I They do not have that ability. I remember looking into a tool a while ago, and it was and actually, you know, at the school, we thought about developing a tool. It would be like a widget on the side that you could adjust on different things like that. You could do, you could remove images, you could remove animation, you could change color, contrast, that sort of thing. And it just be like a very predefined kind of kind of settings. But in my research, I found that a lot of times that causes other problems for people, and it kind of falls into the the arena of. Um, separate but equal. And there's a lot of issues with that right now in the accessibility space when it comes to the web. So for instance, there was a company, I forget what the company name was, but they had one of their things that they did was they would create text only versions of your pages. So you'd contract with them. They would they would scrape the content of your site. They would create a text version, text only version of your pages. So if people were using a screen reader, they could just follow that link and then browse the text only version. And there was litigation, and the company got sued, and the the person suing was successful, because it was essentially creating a separate argument.   Michael Hingson ** 50:34 And that's not necessarily separate, but equal is the problem, because if you only got the text, pictures are put on websites, graphs are put on websites. All of those other kinds of materials are put on websites for reasons. And so what really needs to happen is that those other things need to be made accessible, which is doable, and the whole web con excessive content. Accessibility Guidelines do offer the the information as to how to do that and what to do, but it is important that that other information be made available, because otherwise it really is separate, but not totally equal at   Dan Swift ** 51:11 all. That's absolutely true. Absolutely true. Yeah. So it   Michael Hingson ** 51:15 is a, it is something to, you know, to look at well, you've been doing a podcast and so on for a while. What are some challenges that someone might face that you advise people about if they're going to create their own podcast or a really productive YouTube channel,   Dan Swift ** 51:31 be real with yourself with the amount of time you have to dedicate to it, because what I found is that it takes a lot more time than I originally anticipated I thought going in, I thought, you know, so I typically try to record one or two people a week. When I first started out, I was only recording one person. And usually I would do, you know, record one day, edit the next day, you know, do the web page stuff. I would go with it, you know, I can knock it out in like an hour or two. But I wasn't anticipating the social media stuff that goes with it, the search engine optimization that goes with it, the research that goes with it, trying to so if I'm if I'm producing a video that's going to go on YouTube, what's hot at the moment? What are people actually searching for? What's going to grab people's attention? What kind of thumbnail do I have to create to grab someone's attention, where it's not clickbait, but it also represents what I'm actually talking to the person about, and still interesting. So it's a lot of a lot of that research, a lot of that sort of thing. It just eats up a lot a lot of time when it comes to like the transcripts, for instance, that was those super easy on their number of services out there that created automatically for you, and they just have to read through it and make sure it's okay. I know YouTube will do it as well. I found that YouTube isn't as good as some of the other services that are out there, but in a bind, you can at least rely on YouTube and then go and edit from that point. But yet, time is definitely a big one. I would say, if anyone is starting to do it, make sure you have some serious time to dedicate several, several hours a week, I would say, upwards, you know, probably a good, you know, four to 10 hours a week is what I would estimate in the moment. If you're looking to produce a 30 minute segment once or twice a week, I would estimate about that time.   Michael Hingson ** 53:11 Yeah, one of the things I've been hearing about videos is that that the trend is is clearly not to have long videos, but only 32nd videos, and put them vertical as opposed to horizontal. And anything over 30 seconds is is not good, which seems to me to really not challenge people to deal with having enough content to make something relevant, because you can't do everything in 30 seconds exactly,   Dan Swift ** 53:41 and what I found too. So this was very this was a little bit of a learning curve for me. So with, with the YouTube shorts that you have, they have to be a minute or less. I mean, now they're actually in the process of changing it to three minutes or less. I do not have that access yet, but it has Go ahead, yeah, yeah. Yeah, so. But what I'm finding Michael is that the people that so I might create this a great example. So I was interviewing a comedian in New York City, Meredith Dietz, awesome, awesome episode. But I was talking to her about becoming a comedian, and I made about four different shorts for her from her video, and I was doing a new one each week to kind of promote it. And the videos, for me, they were getting a lot I was getting anywhere between maybe 315 100 views on the short for me, that was awesome. For other people, you know, that might be nothing, but for me, that was awesome. But what I found was that the people that watch the shorts aren't necessarily the same people that watch the long form videos. So I'm or, or I might get subscribers from people that watch the shorts, but then they're not actually watching the video. And in the end, that kind of hurts your channel, because it's showing, it's telling the YouTube I'm gonna use air quotes, YouTube algorithm that my subscribers aren't interested in my content, and it ends up hurting me more. So anyone that's trying to play that game. And be aware of that. You know, you can't get more subscribers through shorts, but if you're not converting them, it's going to hurt you.   Michael Hingson ** 55:05 I can accept three minutes, but 30 seconds just seems to be really strange. And I was asked once to produce a demonstration of accessibe on a website. They said you got to do it in 30 seconds, or no more than a minute, but preferably 30 seconds. Well, you can't do that if, in part, you're also trying to explain what a screen reader is and everything else. The reality is, there's got to be some tolerance. And I think that the potential is there to do that. But it isn't all about eyesight, which is, of course, the real issue from my perspective. Anyway.   Dan Swift ** 55:41 Yeah, I completely agree. I think what YouTube is trying to do, and I believe in getting this from Tiktok, I think Tiktok has three up to three minutes. Actually, there might be 10 minutes now that I think about it, but, but I think they're trying to follow the trend, and it's like, let's make videos slightly longer and see how that goes. So be very curious to see how that all pans out.   Michael Hingson ** 55:58 Well. And I think that makes sense. I think there's some value in that, but 30 seconds is not enough time to get real content, and if people dumb down to that point, then that's pretty scary. So I'm glad to hear that the trend seems to be going a little bit longer, which is, which is a good thing, which is pretty important to be able to do. Yeah, I completely   Dan Swift ** 56:21 agree. Because like that, the trend right now, it's, you know, people, they want stuff immediately, and if you don't catch them in 10 seconds, they're swiping onto something else, which is which is very challenging, at least, especially for me and what I do. Who's   Michael Hingson ** 56:32 the most inspiring guest that you've ever had on your podcast?   Dan Swift ** 56:37 Michael, this is a good one. This is a good one. So the video for Ashley Mason. She is a social media marketing she created a social medi

And as if the above title weren't enough, Paul Hylenski is also a 5-time successful author, a pilot and a public speaker. Paul grew up in Delaware. He joined the Marines in 1999 and stayed with the Corps until 2007. He then left to join a large company and, as he put it, got the opportunity to observe both good and bad leaders. He and I talk quite a bit about leaders and leadership. I asked him if he observed bad leadership in the Marines. He said that people being human do find themselves not leading properly in and out of the marines. His insights about this are best left for him to tell.   Along the way Paul formed his company, Quantum Leap Academy. His company was formed to provide comprehensive training in AI technologies. He also formed VetMentor.ai, a service designed to assist military members in navigating the complexities of disability claims and career transitions with the aid of AI.   As you may be able to gather, AI is a subject Paul has learned a great deal about. He discusses how we all can use it much more than we do in ways that can and will benefit us along our life journeys.   Time passed for me quickly talking with Paul. He would love to hear from you, veteran or not. He has much to offer as you will see.       About the Guest:   Paul Hylenski is a dynamic business leader, software programmer, and motivational speaker with a deep passion for leveraging technology to enhance community and personal growth. After serving in the Marine Corps, Paul founded Quantum Leap Academy, a platform dedicated to providing comprehensive training in AI technologies. His vision extends into healthcare, where he has launched BioMarker Detect, an early cancer detection company. Paul's entrepreneurial spirit is complemented by his authorship, notably of his book 'Error-Proofing Humans,' which explores the intersection of human error and technological solutions. Paul's commitment to veteran affairs is evident through VetMentor.AI, a service designed to assist military members in navigating the complexities of disability claims and career transitions with the aid of AI. His efforts to democratize technology education are also showcased in his development of courses like 'Introduction to AI for Teens' and specialized training for veterans. Outside of his professional endeavors, Paul enjoys piloting aircraft and spending quality time with his family. His forward-thinking approach and dedication to service have made significant impacts across multiple sectors, particularly in AI education and veteran support.   Ways to connect with Paul:   LinkedIn : (1) Paul Hylenski | LinkedIn Website : www.quantumleapacademy.org   About the Host:   Michael Hingson is a New York Times best-selling author, international lecturer, and Chief Vision Officer for accessiBe. Michael, blind since birth, survived the 9/11 attacks with the help of his guide dog Roselle. This story is the subject of his best-selling book, Thunder Dog.   Michael gives over 100 presentations around the world each year speaking to influential groups such as Exxon Mobile, AT&T, Federal Express, Scripps College, Rutgers University, Children's Hospital, and the American Red Cross just to name a few. He is Ambassador for the National Braille Literacy Campaign for the National Federation of the Blind and also serves as Ambassador for the American Humane Association's 2012 Hero Dog Awards.   https://michaelhingson.com https://www.facebook.com/michael.hingson.author.speaker/ https://twitter.com/mhingson https://www.youtube.com/user/mhingson https://www.linkedin.com/in/michaelhingson/   accessiBe Links https://accessibe.com/ https://www.youtube.com/c/accessiBe https://www.linkedin.com/company/accessibe/mycompany/   https://www.facebook.com/accessibe/       Thanks for listening!   Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page. Do you have some feedback or questions about this episode? Leave a comment in the section below!   Subscribe to the podcast   If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can subscribe in your favorite podcast app. You can also support our podcast through our tip jar https://tips.pinecast.com/jar/unstoppable-mindset .   Leave us an Apple Podcasts review   Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts.       Transcription Notes: Michael Hingson ** 00:00 Access Cast and accessiBe Initiative presents Unstoppable Mindset. The podcast where inclusion, diversity and the unexpected meet. Hi, I'm Michael Hingson, Chief Vision Officer for accessiBe and the author of the number one New York Times bestselling book, Thunder dog, the story of a blind man, his guide dog and the triumph of trust. Thanks for joining me on my podcast as we explore our own blinding fears of inclusion unacceptance and our resistance to change. We will discover the idea that no matter the situation, or the people we encounter, our own fears, and prejudices often are our strongest barriers to moving forward. The unstoppable mindset podcast is sponsored by accessiBe, that's a c c e s s i capital B e. Visit www.accessibe.com to learn how you can make your website accessible for persons with disabilities. And to help make the internet fully inclusive by the year 2025. Glad you dropped by we're happy to meet you and to have you here with us.   Michael Hingson ** 01:21 Well, hello everyone, and pleasant greetings to you wherever you happen to be today. I am Michael Hingson, the host of unstoppable mindset where inclusion, diversity and the unexpected meet. It's a lot of fun to be here. I really appreciate you joining us today. Hope that you have as much fun listening as I and our guest have in bringing this to you, I tell everyone who's going to come on the podcast that there is only one rule that everyone has to follow on the podcast or we won't do it, and that is, you have to have fun. And Paul Hylenski is definitely a person who said he would him force himself to do that. So Paul, welcome to unstoppable mindset. We're really glad you're here   Paul Hylenski ** 02:02 today. Thank you so much. Michael, appreciate it. Thank you for having me on Well, Paul is a   Michael Hingson ** 02:08 former Marine. He is the founder and CEO of something called Quantum Leap. He does various things with AI and technology. He is a leader by any standard. He's authored, if I recall write five books anymore, any more coming up in the queue, we'll have to learn about that. But definitely not a person who is idle, a man of action in a lot of different ways. And we're really glad that you're here with us. So why don't we start if you would, why don't you tell me a little bit about you as kind of the early Paul growing up and all that kind of life and all that and how you got started.   Paul Hylenski ** 02:45 So, you know, I grew up in actual Newark, Delaware, so funny, there had a great childhood. Decided when I was in high school that I was going to enlist in the Marine Corps, so I wanted to be one of the few and the proud, and so I joined the Marine Corps, served in the Marine Corps, that was one of the best experiences of my life. Then after the Marine Corps, I actually got connected with a company with that was an aerospace company, and started working there as a frontline leader, and then from there, I saw a lot of bad leaders, and I saw some great leaders. And so I was able to, actually, as I kept going through the ranks, tailor my leadership towards how I wanted to be. And it was different. It was using science, psychology and leadership. And then as the AI revolution started happening, I started actually putting AI into business, and I wrote a book about AI in business, and then I thought to myself, well, now maybe I can impact the world in a bigger way. And that was what kind of drove me to start Quantum Leap Academy. And Quantum Leap Academy focuses on teaching professionals AI that's practical and and then that's really been my passion and mission is impacting the world with actually teaching how to automate and really make your life easier using AI   Michael Hingson ** 04:23 Cool. Well, you've been been doing a lot of stuff. How did you come up with the name quantum leap?   Paul Hylenski ** 04:29 A great story, but back in the 80s, there used to be an amazing TV   Michael Hingson ** 04:33 show, yes. So   Paul Hylenski ** 04:35 I thought, what better? You know, I was looking for a name that showed like, look, we're gonna go from where we're at now, and we're going to take this huge leap, and it's almost a leap of faith, you know, that we can use this new technology in in the forces of good. And so, you know, broke it out from my childhood. But, you know, kind of took the quantum leap. And then, you know, the academy. So, and   Michael Hingson ** 05:02 it kind of went from there, yeah, well, so you said that you left the Marines. Well, when you left the Marines, and you went then to a major company, and you started out in kind of initial leadership and so on, how did being a Marine help you in terms of dealing with an understanding leadership, much less what made a good leader and what made a leader, not necessarily a good leader.   Paul Hylenski ** 05:31 You know, for me, and I've done, I've done a few talks, and I've done a couple TED talks, actually, on this. And for me, the military is is is a great example of what they what I like to call the total leadership. So in business, normally what we do is we only worry about the people when we need them, or while they're at work or while they're accomplishing a mission. But in the military, we have to worry about the total person, because even the person's home life, or maybe things they have going on outside of the mission impact their ability to carry out the mission. And, you know, I've said a couple things you know about just both the military rewards people. So in the military, you get medals, and, you know, you get medals and awards for sacrificing yourself for the good of your people. But in business, a lot of times you get, you know, raises and promotions for sacrificing everyone around you for the good of yourself. And I think that's a flawed dynamic that I really got to see in action in the military, and I brought that into the civilian business life, do you   Michael Hingson ** 06:45 and looking back on it, if you will, and you talked about you saw leaders who were good leaders and not so good leaders in the corporate world. And I don't want to pick on the military, but did you see the same sort of thing at all in the military, or do they really weed out people who don't tend to to do very well in the leadership role? That's   Paul Hylenski ** 07:07 actually a myth. So most people think that there's only great leaders in the military.   Michael Hingson ** 07:15 You did find some that weren't necessarily so, okay,   Paul Hylenski ** 07:18 yes, yeah. And you know, like bad leaders tend to shape us in different ways, and sometimes better than the better leaders. You know, because you learn more from watching people who might be doing it wrong. But you know, it is great learning experience. I learned some things to do, and then I learned some things that did work, but yeah, absolutely, there are bad leaders everywhere. So   Michael Hingson ** 07:43 what would you define as as a bad leader? What are some things that you experienced or you've seen that made people not necessarily such great leaders?   Paul Hylenski ** 07:52 So for me, it's, you know, leading through intimidation and fear that was a practice that was made pretty common all throughout, you know, 1970s 1980s and the myth there was that people stayed because they were okay with the treatment. Well, in reality, the reason why they stayed to endure that horrible kind of leadership was because they had pensions. Well, the world now doesn't have pensions for most part. So people stay because they like the place or they like the culture. You know, another defining factor for me for leadership is, do I feel psychologically safe with that person? Yeah. And, you know, psychological safety and the ability to make state mistakes and the ability to make failures and view them as growth really defines a leader that's focused on the future and not just on the present or the past.   Michael Hingson ** 08:48 In the military, did people have much opportunity when they encountered somebody who wasn't necessarily a good leader to move elsewhere? I would think that that was probably more challenging to do than when you're working for a company, especially a large company, where you could transfer probably easier, is that true?   Paul Hylenski ** 09:08 Yeah, that that is true. So sometimes you had to endure it and and then you make the best out of a situation. And, you know, like I was saying earlier, sometimes that's where I learned, you know, as I was going through things that just didn't work, you know, and the way you talk to people and treat people, and just even the overall demeanor that you have as a leader, you know, matters. And everything you say is a communication, but everything you do is a communication as well. And a lot of leaders don't remember that, or they don't, you know, they don't visualize that I   Michael Hingson ** 09:45 know, for me personally, and you mentioned the whole concept of fear and intimidation, and I've experienced it from time to time for a variety of reasons, being blind and interacting with. People, I faced challenges because people tended to not necessarily view blindness as as they should. And so oftentimes I would have people say to me, Well, you got to work harder and different than everyone else, because you're blind and people aren't going to perceive you as being competent. Well, there's truth to that to a degree, but there are ways to approach that as a leader. And I would think that when you're telling someone all the time, you gotta be better, you gotta be smarter, and so on, as opposed to saying, how do we make sure that you shine as best as you possibly can? And I don't know when I adopted this method of operation, but one of the things that I discovered fairly early on was that as I was managing people, and when I started really hiring people and opening offices for companies, one of the things that I said to people was, look, I'm hiring you because you've demonstrated to me, or you've convinced me that you can do the job. So my job isn't to boss you around. My job is to work with you specifically to see how I can add value to what you're doing to make you the best performer that you can be. And what I discovered is that the people who really got that and understood it and chose to find ways that I could work with them and use the skills that I have, and oftentimes they took the lead in discovering what they thought that I could help with but we worked together, and when they got that concept, they really did perform a whole lot better than those who didn't get it.   Paul Hylenski ** 11:53 That's a great strategy.   Michael Hingson ** 11:55 Well, I think it's and it's important, because I think that fear and intimidation doesn't help anyone, and it doesn't help you or anyone to develop a real trust if you're just dealing with someone out of fear, as opposed to dealing with someone through trust and teamwork, it's a it can be a challenge. Yeah, I   Paul Hylenski ** 12:18 think you know, one of the things that we're finding out more and more and companies are finding out is they never really made significant headway to fix issues or to get real growth because of that fear and intimidation. And I mean, just take, just take mistakes. Right? If I'm afraid to make a mistake, I'm going to lie, cheat and steal my way out of that mistake. I'm gonna blame it on everyone else, but if I'm not afraid to make the mistake, then I'll tell you, as my leader, exactly what happened, and then as the leader, if you know exactly what happened, you can work corrective action and fix it and make the environment better. And that's where the beauty and the secret behind that is   Michael Hingson ** 13:01 well, or the other part of it is because you acknowledge the mistake and so on, the leader will let you do the corrective acting and take the corrective steps that need to be done, because especially that will be a good learning experience for you, but they're there to support you, which is really the issue.   Paul Hylenski ** 13:21 And I think when leaders change their mindset from failure being this negative connotation, and, you know, failure being this bad thing, to, hey, that's just another step towards our growth, you know. But what did you learn from it? Or what are you going to do different, right? All those things, then all of a sudden, people start to realize they're in a growth mindset. They can fail, they can learn, they can proceed, and then they end up growing. Yeah, and   Michael Hingson ** 13:49 I think overall, people really do want to grow. They want to evolve, but the leader is, or ought to be, the person to help really create that environment for people.   Paul Hylenski ** 14:04 Yep, and spot on. I mean, who wakes up in the morning and says, Hey, I'm going to be a loser today. I'm going to be a failure today, right? Nobody, so. But people fail, and people might not get something, they might not understand something, and you're spot on. The leader has to be the one that's their cheerleader or their coach or their mentor or giving them direction on Hey, you didn't really do well on this, but this is what you need to do next time. Similarly, a different way, or   Michael Hingson ** 14:34 you didn't do well. Do you have any idea of why? Because it's always great if you can figure it out. You know, I have worked with guide dogs since 1964 and it took a couple of dogs for me to develop and begin to articulate this. But what I learned is that every time I got a new guide dog, and we would spend time at the school or whatever, what I. Really doing there is beginning the process of creating a bond with a new teammate. And no mistake, dogs are as much a part of a team as anyone else. If you allow that to happen, most people really look down on on dogs, but the reality is that they have a lot of senses, and they have a lot to contribute. And the thing is, if you believe people like Cesar Milano and so on, the thing is, dogs really want to be a part, and they really want you to tell them what you expect from them. And in that sense, it's really cool. They don't have hidden agendas like people often do. And so the difficulty with people with hidden agendas is it makes it more difficult to trust them, and sometimes you can break through that. And the hidden agenda isn't such a hidden agenda that isn't necessarily a negative agenda at all, but we tend to be very closed in terms of trusting others, because we're always concerned about what hidden agendas they have. Dogs, I believe, do love unconditionally, but I don't think that they trust unconditionally. But the difference between a dog and a person is that a dog is generally more open to trust, unless something just really hurt them, which is something typically that it would be a person who did that. But dogs are open to trust. And if you create that trusting relationship, it is second to none.   Paul Hylenski ** 16:34 That's that's interesting. Know that?   Michael Hingson ** 16:38 Yeah, they The reality is that they want to please. They want to do a good job. So I've learned over the years working with guide dogs, it is an extremely stressful job for them, because they want to please. They want to make it work. And they're being tested whenever, for example, the harness is on, even when it's off a lot. But when the harness is on, they watch, and have to watch a lot what's coming up at the street corner, the curb is coming up. I got to stop at the curb and make sure that my person stops at the curb. I tell the dog to go forward, and the dog sees there's a hybrid car coming, and I don't know it, because it's in battery mode and so I don't hear it, but the dog, if I create a good, teaming relationship with that dog, the dog knows that it has the authority to not budge to make sure that we don't get smushed by the car. Likewise, if everything is fine, then the dog will go. But the dog has a lot of decisions to make in the in the guiding process. They don't lead, they guide. It's my job to know where to go and how to get there, and I need to learn that as I travel and make that happen. And the neat thing about it is that when the dog understands I'm doing my job, it feels a lot better about doing its job, and it knows what its job is. And in reality, what that ultimately means is that we form a good team, supportive relationship. And I think that is something that because just as relevant in person to person, leadership and teamwork as it is in person to dog relationships, oh sure,   Paul Hylenski ** 18:27 the ability to trust each other and feel safe with each other, absolutely. Yeah. So,   Michael Hingson ** 18:33 so you've done a lot. What got you started in dealing with AI? What? What attracted you to that? Yeah,   Paul Hylenski ** 18:40 yeah. My fourth book was actually titled The evolution of leadership. So aI had just kind of started coming online. I started researching AI, and then I thought to myself, Okay, well, now that I've researched it, I'm going to start actually using it. And then I went to actually input it into a few businesses, and once I realized, like, wow, like, I could automate 50 to 60% of the business with AI. And I started noticing, like we had time to be proactive, not reactive. Then, then I realized, okay, I'm we're on to something most anybody. If you ask them about AI, they're just going to say, chat, GPT. But there's, you know, 1000 different platforms. There's AI automations. So I thought, Okay, people just don't know. And, you know, the more senior people are, the least, the less that they knew about, you know, AI and chatgpt and everything. So I thought, Okay, well, the, you know, baby boomers and a lot of the you know, millennials, they're running companies right now, or they own companies, but they're the ones that are not able to really use AI or new AI. So you. Know, I've really tried to put a focus on teaching practical AI. So not just the, not just the theory and all the, you know, school type of material, but actually how to utilize AI to benefit you and your business. And that's been, you know, really fantastic since we kicked the academy off, we've gotten formally accredited. So when you take, you know, certifications, one thing that's different is a lot of places you'll take AI certifications, and you just get a little certificate, but no credits, and it's not formally accredited. And that was one thing we put a lot of attention into because as business professionals, the whole point of taking training is to grow in your, you know, career and grow in your job. So, you know, accreditation and credentials matter. But, yeah, that's what got me started, and then now it's become a passion. I, you know, I do free training for veterans. We actually even started a software as a service to help veterans put their disability claims in and streamline that process. So it's been it's been really fantastic. AI has opened up a lot of opportunities. How does AI   Michael Hingson ** 21:18 help in that whole process of doing the claims, applications and so on. What does it say? So it's   Paul Hylenski ** 21:23 absolutely great. So this was our startup company, which was a derivative off of Quantum Leap, and it's called vet mentor AI, so we'll be releasing it towards the end of the year, and we've already used, utilized it on, you know, test veterans, where they've actually allowed us to help them put their applications in. So the problem is that, you know, for first time submittals for veterans, it's a 70% rejection rate rate, so a lot of veterans either don't know what to do, or maybe they're afraid to do it. And then one of the big things is PTSD and anxiety. There's a fair amount of veterans that really have high anxiety, or maybe have issues from their PTSD, where this process is daunting and the fact of going in front of a medical examiner is almost impossible for them. So the way it does it, or what it does is it allows the veteran to basically in plain language, right? What's wrong? So they'll fill out a very simple form. It's something that you know, someone with basic education can fill out, and it's basically a questionnaire. And then we have a proprietary AI software that we actually built that analyzes all that data, and then it's trained on the VA rating manuals. It's trained on the VA forms, the VA website. And so what it does is it actually tailors the person's claim to the VA rating manual. And by wording it like that, it actually allows the veteran to get this comprehensive report, which even asks the person, Hey, did you have this medical documentation? Did you think about filing for this secondary claim and and so then the second part of this is we actually built an AI platform to allow the veteran to do a simulated CNP exam. So what a cmp exam is, it's a medical exam where the veteran has to go in and actually get examinated, and you know, then that that doctor will determine if they, you know, meet the criteria. So what we've done is we've actually utilized AI and allowed them to do their medical examination with an AI. It even has a voice, so that they can talk to it like a person and imagine and this has been wildly successful for our veterans that have high anxiety or PTSD, because they're able to practice their their CNP exam, and you know, it will critique their answers. It will let them know, you know, what, what their rating would be, and all this thing in the background. And it's really amazing, because then when they go in for their real one they've already practiced, and they are less anxious, they're less nervous about it, and they make better decisions. So the one great thing, and I'm so proud of this, because being a veteran, this was something that was really hard for me, was, you know, submitting my disability claims, so the average failure rate is 70% on the first time submission but with vet mentor, all of our veterans, we are currently at an 80% acceptance rate on first time submittals. So we've flipped the strip the script, and you know, instead of a 30% approval rate, we're up to an 80% approval. Boring and   Michael Hingson ** 25:01 it's interesting, because what I'm really hearing is that, to a large degree, the AI system is helping to train, much less helping to create the actual information that has to be submitted. So it's kind of a double pronged approach to solving a problem,   Paul Hylenski ** 25:20 yeah, and it's, it does it. It prompts them for, you know, something simple that I never realized in the beginning of the process was a personal statement. So it helps them to actually generate a personal statement about their illness or injury or disability. And then, even more than that, it prompts you to put it in the proper form. So most veterans don't know, but if you don't upload your personal statement in the 4138 Bravo form, they actually discount it. And there's a lot of veterans that are are submitting just a Word document with a little handwritten thing, but it, you know, the AI, actually, when we started doing this, the AI picked up that, hey, this must be done in this form. And when we were looking at it, we were like, Oh my God. We didn't even know that. So the AI taught us when we were actually making it   Michael Hingson ** 26:13 well. And how long have you been doing this? So   Paul Hylenski ** 26:17 we've been doing this for four months. Little over 20 veterans. So we're in the middle of, we're in the middle of the end stages of, you know, building the rest of the site and the platform. We basically, when we started, we kind of had three or four different types of AI systems talking to each other. So we're actually building and consolidating it just into one that's a nice little format for a user. And the beauty part with with our software is it's a one time lifetime fee, so you pay $50 which covers the cost of the AI software in the background, and you have it for life. So as your your disabilities get worse with age, because we all know they do. You have the software for the rest of your life, and it's for only $50 which is starkly different than the A lot of the companies out there, which you know they're preying on veterans. And what they do is they take 1000s of dollars or percentages off of their disability every single month. So that's one of the things that we wanted to do when I made this company. It wasn't to make money, it was to impact the world. So that's why we keep it just as a lifetime fee, just a $50 one time, and you're done. So the veteran basically just pays for the software is   Michael Hingson ** 27:43 bit mentor, a nonprofit like a 501 c3 company. So no,   Paul Hylenski ** 27:47 we're not right now. We haven't done any of that yet, just because we want to build the platform,   Michael Hingson ** 27:54 it's fair. Um, you've got to start somewhere, needless to say. So   Paul Hylenski ** 27:59 we've helped. We've helped over 20 veterans so far. So that was the big thing, was we get we got veterans in the beginning that we're like, Okay, well, let's try it out. And then, you know, we've done a couple pitches. We've, you know, been getting investments in, in the platform and everything. And the intention is, you know, I want to roll this out nationwide to help veterans. There's a little over a million pending disability claims right now, and if you just go off of the you know, the standard statistics, 70% of them will get rejected. Yeah, and that is a horrible thing for a veteran who maybe is having trouble at work, or maybe their disability is impacting their ability to get promoted and and to have to go through that after they've honorably served the country. You know that I'm trying to fix that?   Michael Hingson ** 28:53 Do you see expanding this and also working with people who aren't veterans by any chance?   Paul Hylenski ** 29:01 So we haven't thought of that. But that is a great idea. I was actually so we, we're in the VA Pathfinder system, because my intention in the beginning was actually to partner with the VA, because imagine a VSO, or, you know, one of the members from VA who are helping the veterans have this tool to help them. You know, I think that would change the game too   Michael Hingson ** 29:26 well. I'm thinking, for example, there are a lot of people with disabilities who have to navigate and interact with their state rehabilitation systems and so many other things that might very well benefit from what you're doing and also who will learn a lot, and that will help them with their confidence as well, which is kind of what prompted my my question, and my thought about it like   Paul Hylenski ** 29:50 we haven't yet, but you got my mind thinking now, and you know what happens when that,   Michael Hingson ** 29:54 there you go, yeah, well, that's, that's always, that's always a good thing, not. A problem. So when you started really integrating AI into healthcare and doing the things that you were doing, what kind of challenges did you run into, or are you running into?   Paul Hylenski ** 30:13 Yeah, the first one was when I started integrating it into business, I met a lot of resistance, because people don't understand it. So even something as simple as chat GBT, right? Just go real basic into AI. Chat GBT. There's so many people right now that either haven't used it or are not using it or don't even know all of the things that it can do. If you have a business, if you're a business owner, if you're a manager, if you are doing office clerical work, chat, GPT can probably boost your productivity just by 30% and you know, I mean instantly you will feel the benefit. I use it to write emails. I use it to do charts, data analysis. You know, there's a there is so many uses. You know, you can use chat GBT to build a game show that then you can use that game show to go train people on Excel. I mean, it's amazing the amount of limitless things that you're able to do with it. But chat TBT is literally like one grain of sand in the beach that is AI, and most people don't know that. You know, there's another platform that's make.com it literally builds automations. So this call our podcast right now, you could have an automation that it would literally transcribe the the podcast, then it could send it into four or five different directions. We could do Google Doc, we could do a Google sheet, we could put a summary about it. It would do everything all in one just by hitting one button. And so businesses are starting to use this because it's automating most of the clerical work that they do.   Michael Hingson ** 32:04 I know that I'm not using AI nearly to the extent that I could even chat GPT, and part of it has been that I've found some inaccessibility issues in some of the buttons that aren't labeled and so on. So gee, maybe I'll have to talk into giving me a better lesson on using some AI stuff, but I appreciate and understand the concepts of it, and so I know what you're saying, and I've used it to write articles in the past. And what I do when I when I bring AI or chat GPT into it, is I'll tell it to write something, and then my job is to look at that and massage it and make it my own and add my own stuff to it. And in fact, I've I've actually told chat GPT to create something, and I've told it to do it six or seven times, and I take the best of all of those, plus what I contribute to it, and turn that into the article that I actually publish. But the I think the most important part about it is that I really know what it's it's doing, and what I'm doing, and I know that I have to be the one to control it. I can't just go off and let chat, GPT create something and then submit it. That's not only worthless, but it's it's certainly dishonest. I've said many times. You know, teachers talk about students that use chat GPT to write their papers and all that, and then they turn them in, and sometimes you can tell that they're written by chat GPT, and sometimes you can't, but teachers are worried about that. My reaction, and I have a secondary teaching credential, so I do understand something about all this. But my reaction is, I think that for chat for teachers, chat GPT is great if kids go off and write their own papers, great if they use chat GPT to do it. Great because at the end of the day, you turn the paper in, and then the teacher calls you up during a period and say, not offend your paper, you're going to know real quickly who really did the work and who didn't. Yeah,   Paul Hylenski ** 34:11 and, and, you know, you brought up some good points there, right? So I have a, I have a colleague on LinkedIn who's the AI educator, and so what he actually has done is he's put a lot of AI into education, and there are softwares that a lot of teachers are using now that actually detect chat. GBT, yeah, detects AI. You know, one of the best things that people can do, and this is something that most people know nothing about, but you can actually create a digital twin of yourself, and it's very easy to do on open AI, so you can create an assistant that's actually trained on how you write, how you sound, right? And so this, we did this very easily for me, where I. Downloaded all of my posts, all of my interactions, and everything from LinkedIn, and I trained it on all of my books. So what happens is is you literally have an AI system that talks like you, has your same tone, has the same humor that you do. And when I do my posts and everything I do kind of the same thing you do, where I'll have my digital twin create the post and then I massage it or whatever, or go through it and read it. But what I've found is definitely for automations and definitely for email writing, these digital twins that you're able to create for particularly marketing as well. They're pretty spot on. I mean, you would have a hard time telling the difference between my digital twin and my writing. Of   Michael Hingson ** 35:48 course, you're leaving yourself open to the obvious question, which one are you the twin or the real person? But that's okay, yes,   Paul Hylenski ** 35:56 that's a good one today. Are   Michael Hingson ** 35:59 you a robot or not,   Paul Hylenski ** 36:01 no. But people don't realize that. And you know, the beauty part of it, Michael is like, so if you own a small marketing company, I mean, you could create 30 to 60 days of content in literally a couple hours. If you have a digital twin, and it changes the game, because you're able to scale businesses, you're able to do things. You can set automations up. You know, on some of my emails, particularly my personal emails, depending on what is in the email, I have automations where the AI actually responds to the email and it sends it to my drafts and then, so at the end of the day, we do as I look at the draft email. I click it, I click it, I click it up. I don't like the way that read it. I'll delete that and write it for real. But for the most part, I'd say it's about 90% perfect. And you know, I took, I take maybe about two hours of emails and turn it into about 1520 minutes. And so then it gives me an extra hour and some change every single day just on that task.   Michael Hingson ** 37:06 So here's a question, actually. So you do the process that you just described, and you go off and you massage some of the emails because you didn't like the way your twin created them. How do you then make sure that your twin gets trained on your changes.   Paul Hylenski ** 37:23 Plus, you know, I mean, you That's exactly it's the whole point is you have to what I'll do is I'll basically copy and paste the email, put it into my digital twin and say I did not like maybe the word, a couple of the words they used, or I didn't like the tone of this email, and so that's the beauty part with chat. GPT, yeah, and you know, any, pretty much, any, AI, the whole point of it is fine tuning it, so you have to, but most people don't realize that you can talk to the AI because it responds. So like, if you say, I don't like this, it's not going to do that, and it's so important, and one of the hacks that a lot of people don't do. So when I create something, let's say a business plan or a coaching plan, and I'll create it, I'll ask chat GBT to critique it for me and then improve it. So now I have it created, then I have it critique it and improve it, and pretty much, at the end of that, I have a pretty perfect document. And that's changed a lot of the the ability that I but most people don't realize you can actually have it critique its own work,   Michael Hingson ** 38:36 yeah, and that's and that's the reason I asked the question, because that's really the whole point. It is a, it is a process, and AI is opening so many things. I work with a company called accessibe, and accessibe uses AI and what's, what's called a, well, it's, it's a, it's a process where it can generate the code that will make a website more accessible, called an overlay. Some people say they don't work and so on, because they believe that you got to manually code it. But in reality, I can find manual coders who don't always do a good job. But what accessibe does is that they have created a system out of necessity. They're in Israel, and in 2017 Israel said, websites need to be accessible. And these guys that all started this company in 2015 and the company was making websites for people, well, suddenly they had to make everything accessible. And they created an AI process that does a lot of that. It's expanding and it's improving over time, because there are things that it it didn't do well, and there are things that it will get better at as it goes forward. But the fact of the matter is that it does help make websites a lot more inclusive than they ever were. So for example, if you're a person with epilepsy and you go to a web. Site that uses accessibe, and there are blinking elements on that page that could cause you to have a seizure. You can go into a particular disability profile on accessibe That's for people with epilepsy, and disable those blinking elements. And the way it all works is that accessibe's widget transmits the code not to the website and modifies the website code. It transfers the information directly to my browser and and my browser and my screen reader that verbalizes to me doesn't care where the code comes from, as long as it's there. So it's really pretty clever, and it and it's and it's making quite a difference. It's got a long way to go, but AI is new autonomous vehicles have a long way to go. They're pretty new, but they're getting better. So it's, it's a process, right?   Paul Hylenski ** 40:52 We're at the beginning of this, and it's, you know, starting to really grow. And so, like, you know, people, people just, you know, a lot of people are still resistant to it and, and there's good reasons for that, right? I mean, this is going to be very dangerous as much as it's going to be good, right? I mean, with the deep fakes and all the ability that you allow people to do with it, they but there's that much good with it too and knowing it. And once you start knowing it and knowing what to look for and learning it and everything, then you can start to pick up on maybe some not so good ways of using it, or, you know, the ethics about it, or, you know, the transparency about Yeah, how do   Michael Hingson ** 41:38 you balance the technological innovations and the ethics in, in what you do, yeah,   Paul Hylenski ** 41:45 for me, so that's part of what we teach in the academy. So like, the first and I have five levels there. Each level goes up, but in, in the first level, it's all about, like, AI and business. So there's a fair amount of, you know, ethics, transparency and everything about proprietary data, not putting certain data into it, you know. So for me, it's that is the biggest key, because especially with vet mentor, you know, you're dealing with really touchy areas, medical information and everything. And, you know, while it's kind of sanitized because of our process, you know, it's still it's new. And, you know, and with anything new, there's going to be some type of resistance, there's going to be questions, and people with the lack of information, they make up their own, right, and that's where you get a lot of the confusion about AI right now, but I think it's important to realize that, you know, this is new, so you have to tread carefully. And you know, the best way to actually protect yourself is to educate yourself, yeah, um,   Michael Hingson ** 42:55 and, you know, the internet and itself, it's got the dark web, and the web that's not so dark, and there are, there are going to be people who will misuse it, but what we we need to learn is how to bring ethical decisions into it, and over time, hopefully, we can bring down a lot of The the so called Dark Web, and let people know or or get people to understand that's inappropriate behavior. And I think the same thing with AI. And yes, you're going to see people who get fooled. You're going to have a lot of challenges, but there is so much positivity that can come from it that is is even more important than the negative parts,   Paul Hylenski ** 43:41 yep. And I think, you know, there's, there are companies out there, because I've talked to a couple of their CEOs that are actually building AI systems to detect negative AI, right, like, so they can detect the deep fakes and everything. And, you know, AI the one, the one touchy thing that it's done so in the in the past, you know, before the internet and everything, if somebody wanted to steal from you, they had to walk up to you and steal from you. They had to pick pocket you, or actually rob you. So you got to see the person's face as they were taking something from you. When the internet came, you had hackers that had no face, right? He was just this person on the other end of the computer, and they could steal your information or steal your money. Well, the problem with AI in this manner is, and why we have to be careful and we have to protect against this is, now it's your daughter. Now it's your husband, your wife, your boss, that comes on the screen and says, I need you to make this transfer. I need money, right? And it's really the thieves, but they've been able to clone, you know, your family member, so now the people stealing from you look like and sound like people that. You care about, and that is why it is getting drastically more difficult to identify some of these, you know, really tough ways that it's being used. So I'm excited to see the innovation that keeps us going to come out, you know, with some of these companies to actually screen for those deep fakes, because then I think once you can get rid of or regulate some of that negative usage, then people really will just focus on the positivity that it gets.   Michael Hingson ** 45:29 Yeah, because the reality is that it can be so positive for everyone, and that if people really learn that and catch on to it and ethically use it, there's, there's no end to the capabilities and the positive things that they can bring about.   Paul Hylenski ** 45:48 I mean, you have 10 year old children now coding websites because they've made it so easy they can literally type in to code a game. People are making their own games. You can go on Claude AI and literally make a web application. Just by saying, make a web application for a loan calculator. So you can create anything in the world. And before, I used to have to know how to code if I wanted to make something like that. Now I just type in what I want, and it spits it out,   Michael Hingson ** 46:20 yeah, yeah, and it's it is going to get better, which is really what makes it so cool. And I hope that people will catch on and understand that being positive and doing it ethically really is better and worth more than than the alternative.   Paul Hylenski ** 46:39 And I think so too. I think once we figure ways to have the AI protect against the AI, I think, I think it'll be even better, too. And, you know, I'm excited, because from the students that I've had in the academy, so many people from beginner level to where they thought they knew, you know, they thought they knew chat GBT. They thought they knew automations. It's been great because you see the light bulb click on, when some people are like, Oh, my God. Why was I taking a week to do that? And you just did it in five minutes. And you know, our level four is where you actually learn how to build a software as a service. And you know, our students walk away with a fully functional AI business. And there's not many schools, there's not many academies that you'll ever walk away with actually real practical knowledge or a real business.   Michael Hingson ** 47:38 Yeah, and that's what makes it so cool, and it it certainly helps to empower people a lot, doesn't it?   Paul Hylenski ** 47:45 Yeah, I mean, we had a school teacher build a CRM platform that then she took and she went and sold it to five different companies, and they're using her platform that we built in two days with AI, it was so crazy. And she's like, I never thought I'd be able to do something like this. And it's true, because five years ago, she would have never been able to do that, because that wasn't her specialty. Right now, you know, she built a fully functioning Software as a Service, and it was, it was the most beautiful thing to see. Her eyes light up at the end of it, where it was, like, I just built this.   Michael Hingson ** 48:24 Yeah, it is so cool that she's recognizing that she's still the one who did it and she used tools, but she's still the one who did it,   Paul Hylenski ** 48:34 yep, yep. And it's, that's really what's amazing is you can, you know, you show people, I bring up, you know, a lot of examples, but most, most people don't realize what they actually have the power to. And a lot of people come on, especially the level one people come in and say, I can't learn this. This is just so hard for me. And then once you start breaking it down to a very simplistic level of, hey, this is how to prompt. This is how the system reads your words. And once you understand that, then everything else starts to make sense. And it's so beautiful, because you have people, you know, creating things they never thought they could before, yeah. And   Michael Hingson ** 49:20 that's what makes it so fun. And people do want to be creative, which is great. You've written several books. I know one you've written. I'm intrigued about. We haven't discussed it yet, error proofing, humans Tell me about that.   Paul Hylenski ** 49:33 Yeah, so error proofing, I love the title. Oh, it's great. And, you know, I got so many comments on that so that book, actually, I'm so proud of it, because it was an Amazon bestseller. You know, I've been on a book tour with it and everything. So I originally brought that book up because I thought, okay, error proofing humans there. So everybody you know commented and said, You can't error proof a human. That. Is the whole point of the book. So every human in the world makes anywhere from three to five mistakes per hour, if they're trained on a topic. Now that goes up by 11 times, potentially if they're they're not trained. So you have people every day making mistake after mistake. Now, most of them are what they call micro mistakes, and they're detectable, right? So you can detect, okay, I typed in the wrong letter, so I hit the backspace or whatever. But when you're doing some tasks, if you have that many mistakes, sometimes you don't detect them, or sometimes you can't correct them, and that's when we have accidents and injuries and everything. So the whole point of the book is, what if you could error proof processes and finally make an error proof human so what we do is we follow, and I did all the in the book. It's all the science and psychology behind human error, how to eliminate it or mitigate it. And one of the one of the key strategies that I'll leave with, like your viewers and listeners, is the Swiss cheese method. Now you can use this in your in your house, you can use this in your business. And it was made up by air, created by a guy named James Reason. And what he said was every process was like a piece of Swiss cheese. It had holes that the error or the accident could go through. So the only way to truly error proof human is to layer peace upon peace upon peace. And every failure you have means that the process isn't robust enough, so you have to add another layer of process. And what happens is, after a while, just like pieces of Swiss cheese laid up on after each other, the holes don't line up after a while, and all of a sudden you have error proof humans. And so we've done this in multiple businesses, and it has transformed their quality numbers. It has transformed their safety numbers. And what happens is, and when you can get people behind things like this, you know, you change the entire culture of the of the company or the business, or even at home. You could do these things that I say it in the book. You can do this with your children. You can do this with yourself, right to to make less and less mistakes. And you know, one of the things that a lot of people don't realize too, one of the other key main things, and then I'll get off the book, but one of the key main things the book is, you know, a high frequency, low risk activity like walking. So 30% of all injuries in a workplace are slips, trips and falls. And you'd ask yourself, well, how come people can't walk? Well, they can walk, right? But, well, I don't look at my feet when I walk, because it's a high frequency low risk, so my mind becomes immediately complacent. But if I were to drive a fork truck, or, let's say, operate a crane with a heavy load, every little sound that thing makes, I'm going to be on super high alert so people don't typically get injured on those high risk, low frequency jobs. So what you have to do in a workplace is you actually have to change the risk dia or dynamic to make it feel more risky. And by layering process after process, and sometimes check after check, you increase the risk profile, which decreases complacency,   Michael Hingson ** 53:44 yeah, which makes perfect sense, doesn't it? Yep, and, and I think that that in reality, we take so many things for granted. Gi, I don't know. I think there are a lot of drivers out there who consider driving like walking. It's high frequency and low risk, and it's not. And the way they drive, though, you'd think they think otherwise, yep,   Paul Hylenski ** 54:06 and that's why there's a lot of accidents, you know, but, and you know, there's a study that said the most accidents happen closer to the person's property, closer to the person's house. And you know, when you look at that, it's because I'm getting closer to home. I'm comfortable with the area. I become more complacent, and now I might run through that stop sign, or I might, yeah, make that turn a little faster than normal. So it's it's really important in an environment, and as we as leaders craft our environment. We need to look at the risk profile. We need to look at our processes.   Michael Hingson ** 54:47 It's also true that what we have to do is to learn to be more disciplined about what we do. And I think that's a lot of what you're saying. When you get closer to home, you tend to be more undisciplined, but you've got to keep the discipline. Plan all the way through the process? Yeah, absolutely. And that doesn't necessarily always happen. Were you a pilot when you were in the Marines? No,   Paul Hylenski ** 55:10 so I was a, I was actually worked on helicopters in the Marine Corps, and then after the Marine Corps, I said, you know, I want to, I want to fly and and so I got my pilot's license. It was one of the best things I ever did in my life. And, you know, it taught me a lot about complacency, because being a pilot and checklists and everything, the entire cockpit is designed to defeat complacency, yeah, and, you know, but I was telling a story last week, you know, the most deadly time for a pilot is between 250 and 500 hours. And you think to yourself, again, these are experienced pilots, like, why would somebody, you know, be more dangerous than than a brand new pilot? And it's because of that risk protein as a brand new pilot, everything matters. I'm going through every single checklist item, every noise that the aircraft makes. I'm hyper vigilant. But after about 250 or 250 to 500 hours, now I'm confident. I'm used to the plane. I'm we might skip my checklist, I might do something riskier than normal, right? And that's the complacency death trap, right there.   Michael Hingson ** 56:28 Yeah. And so after 500 hours, you have done it enough that, in theory, it dawns on you. I've got to stay disciplined. I've got to do this the right way, like I did at the beginning, and it makes me safer, and it makes the flight safer.   Paul Hylenski ** 56:45 Yup and, and sometimes, and a lot of pilots have told me that sometimes during that little 250 to 500 you have a lot of near mistakes or mistakes that you learn from pretty quickly. Yeah and, and then that's enough for them to say, Yep, I gotta break myself of this. Yeah,   Michael Hingson ** 57:05 exactly, right. Well, and we're we're seeing so many things at airports now. It's crazy. I don't understand how so many airplanes either collide with each other, or other equipment collides with them and so on. How come we're seeing a lot more of that than we used to   Paul Hylenski ** 57:22 think. Well, I have to be honest, I think as the travel keeps getting more and more, right, you're going to probably see a lot more of this, because it's taxiing. So taxiing for a pilot is at one of those low risk, yeah, high frequency things, right? I'm just, I'm literally down, I'm not in the air. You feel safe because you're on the ground. You're, you know, you're steering it. And a lot of times, they're also very task saturated while they're taxiing. Yeah, so one thing most people don't see is while they're taxiing, they're going through checklists, they're prepping. And, you know, you don't have a good view of around you in the cockpit. You only have a window that you really can't see in the back. And you know, so the reduced visibility, the high you know, high task saturation, and then that, you know, high frequency, low risk. It's perfect environment for complacency to crop up   Michael Hingson ** 58:20 well. And the reality is, a lot of times it's not a pilot's fault that something happened. They're also relying on other people, whether it's air traffic controllers or whatever. And so there are just a lot of issues, and I think that it is something that hopefully National Transportation Safety Board and the FAA and so on, will work more on to try to eliminate more of those accidents. I have a friend whose daughter went on a vacation last Saturday with her husband, and as they were backing away from the terminal, they got hit by some sort of piece of equipment, and it to late, everything by a day. I don't know any of the details, but just so many of those things happen. We we've got to not allow things to be taken for granted. But I, I would not at all say it necessarily wasn't any way a pilot error, because there's no way to for me to know that, and it probably wasn't, but it still happened, which is, which   Paul Hylenski ** 59:19 is, there's humans everywhere. So humans are prone to mistake. And you know exactly the point of the book is, you're never going to error proof a human, but you can air proof processes. Yep,   Michael Hingson ** 59:32 you can do that. Well, if people want to reach out to you and learn more about you, what you do, maybe become involved in your courses and so on. How do they do that?   Paul Hylenski ** 59:41 Yes, so the best, and I love for people to do this. I have a fantastic network and a community on LinkedIn. So the best way to reach me, and you can reach me personally, is through LinkedIn. Just look up my name, Paul Hylenski, and then if you are interested in. Learning. Ai Mike, it's Quantum Leap Academy. So it's www, dot Quantum Leap academy.org, so it's gonna be.org yeahlin ski   Michael Hingson ** 1:00:12 for me,   Paul Hylenski ** 1:00:12 please. So, h, y, l, e, n, s, k, I,   Michael Hingson ** 1:00:17 so, Paul Hylenski on LinkedIn, which makes sense? Yep, and that's it cool. Well, I want to thank you for being here and being a part of this today. It's been educational for me, and it's been a lot of fun. I value the time that we spent, and maybe in the future, if you think we ought to talk some more, I'm always glad to do that. We can, can do more of this, but I really appreciate all the sound knowledge and advice that you shared, and I hope everyone out there listening and watching appreciated it as well. Love to hear from you. If you would let us know what you thought about our podcast today, you can reach me through email, Michael M, I, C, H, A, E, L, H, I at accessibe, A, C, C, E, S, S, I b, e.com, or go to our podcast page, www dot Michael hingson.com/podcast, Michael hingsons, M, I, C, H, A, E, L, H, I N, G, s, O n.com/podcast, wherever you're listening, though, we hope that you like this well enough that you'll give us a five star rating as a review. We really value your reviews. We love them. Please give us a review. And if you've reviewed us on earlier podcasts, don't stop. We'd like to hear it about this one too. We really look forward to your comments and your thoughts. If you know of anyone who ought to be a guest, and Paul you as well. If you think of anyone else who you think ought to come on our podcast, we'd love to hear from you. We're always looking for new friends to make and new people who have stories to tell. So feel free to do it, and we, we'd love to to hear from you in whatever you do. So Paul, again, I want to thank you for being here. This has been absolutely a lot of fun and and I hope we get to do more of it in the future. Yeah. Thank   Paul Hylenski ** 1:01:59 you so much. I really appreciate the opportunity, and this has been great. Thank you, Michael,   Michael Hingson ** 1:02:07 You have been listening to the Unstoppable Mindset podcast. Thanks for dropping by. I hope that you'll join us again next week, and in future weeks for upcoming episodes. To subscribe to our podcast and to learn about upcoming episodes, please visit www dot Michael hingson.com slash podcast. Michael Hingson is spelled m i c h a e l h i n g s o n. While you're on the site., please use the form there to recommend people who we ought to interview in upcoming editions of the show. And also, we ask you and urge you to invite your friends to join us in the future. If you know of any one or any organization needing a speaker for an event, please email me at speaker at Michael hingson.com. I appreciate it very much. To learn more about the concept of blinded by fear, please visit www dot Michael hingson.com forward slash blinded by fear and while you're there, feel free to pick up a copy of my free eBook entitled blinded by fear. The unstoppable mindset podcast is provided by access cast an initiative of accessiBe and is sponsored by accessiBe. Please visit www.accessibe.com . AccessiBe is spelled a c c e s s i b e. There you can learn all about how you can make your website inclusive for all persons with disabilities and how you can help make the internet fully inclusive by 2025. Thanks again for Listening. Please come back and visit us again next week.

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Here's what chat GBT wrote about today's podcast. This morning on the Mai Morning Crew, we dove into a deep (and slightly quirky) debate. You’ll be surprised by some of the answers! We also took on an accent challenge that left us sounding... well, interesting. And, of course, we uncovered some of the most absurd reasons people have had to make an unexpected U-turn. It’s the kind of show that’ll make you laugh and think—sometimes at the same time!

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Send Everyday AI and Jordan a text messageThink AI is hitting a wall?

Tell us what you think about this podcast!In this series, Bishop Rader Johnson teaches that God is working on us to get us ready for the Rapture. As we grow in this saved life, we must strive to get to a point to where Satan cannot use anything within us to cause us to fall into temptation. In order to do this effectively, we not live in our feelings and emotions, and allow all of our senses to be influenced by the power of the Holy Ghost. Learn more in this important series for our saved lives!For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!From the foundation scripture in Hebrews 6:1, "Therefore leaving the principles of the doctrine of Christ, let us go unto perfection..." Bishop Rader Johnson teaches on the importance of spiritual growth and progression. Tune in to learn how you can grow from glory to glory in God. For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!Now more than ever we as saints should be looking for the coming of the Lord because he can come at anytime. God is coming back for a church who has made herself ready and has not spot or wrinkle. Join for this lesson taught by Bishop Rader Johnson about the Coming of the Lord. For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!This episode highlights Ezekiel's River as taught by Bishop Rader Johnson.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson emphasizes the qualities God seeks in His faithful servants: availability and reliability. He explains that the best dependability comes from making ourselves available to God. Whatever role we desire to fulfill in the church, God will equip us with the ability to do it if we remain available and reliable.  We are cautioned against becoming too absorbed in the busyness of life, reminding us that our devotion should always prioritize the Lord. Tune in for encouragement and practical insights on living a life of faithful service to God.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

If you're in SF, join us tomorrow for a fun meetup at CodeGen Night!If you're in NYC, join us for AI Engineer Summit! The Agent Engineering track is now sold out, but 25 tickets remain for AI Leadership and 5 tickets for the workshops. You can see the full schedule of speakers and workshops at https://ai.engineer!It's exceedingly hard to introduce someone like Bret Taylor. We could recite his Wikipedia page, or his extensive work history through Silicon Valley's greatest companies, but everyone else already does that.As a podcast by AI engineers for AI engineers, we had the opportunity to do something a little different. We wanted to dig into what Bret sees from his vantage point at the top of our industry for the last 2 decades, and how that explains the rise of the AI Architect at Sierra, the leading conversational AI/CX platform.“Across our customer base, we are seeing a new role emerge - the role of the AI architect. These leaders are responsible for helping define, manage and evolve their company's AI agent over time. They come from a variety of both technical and business backgrounds, and we think that every company will have one or many AI architects managing their AI agent and related experience.”In our conversation, Bret Taylor confirms the Paul Buchheit legend that he rewrote Google Maps in a weekend, armed with only the help of a then-nascent Google Closure Compiler and no other modern tooling. But what we find remarkable is that he was the PM of Maps, not an engineer, though of course he still identifies as one. We find this theme recurring throughout Bret's career and worldview. We think it is plain as day that AI leadership will have to be hands-on and technical, especially when the ground is shifting as quickly as it is today:“There's a lot of power in combining product and engineering into as few people as possible… few great things have been created by committee.”“If engineering is an order taking organization for product you can sometimes make meaningful things, but rarely will you create extremely well crafted breakthrough products. Those tend to be small teams who deeply understand the customer need that they're solving, who have a maniacal focus on outcomes.”“And I think the reason why is if you look at like software as a service five years ago, maybe you can have a separation of product and engineering because most software as a service created five years ago. I wouldn't say there's like a lot of technological breakthroughs required for most business applications. And if you're making expense reporting software or whatever, it's useful… You kind of know how databases work, how to build auto scaling with your AWS cluster, whatever, you know, it's just, you're just applying best practices to yet another problem. "When you have areas like the early days of mobile development or the early days of interactive web applications, which I think Google Maps and Gmail represent, or now AI agents, you're in this constant conversation with what the requirements of your customers and stakeholders are and all the different people interacting with it and the capabilities of the technology. And it's almost impossible to specify the requirements of a product when you're not sure of the limitations of the technology itself.”This is the first time the difference between technical leadership for “normal” software and for “AI” software was articulated this clearly for us, and we'll be thinking a lot about this going forward. We left a lot of nuggets in the conversation, so we hope you'll just dive in with us (and thank Bret for joining the pod!)Timestamps* 00:00:02 Introductions and Bret Taylor's background* 00:01:23 Bret's experience at Stanford and the dot-com era* 00:04:04 The story of rewriting Google Maps backend* 00:11:06 Early days of interactive web applications at Google* 00:15:26 Discussion on product management and engineering roles* 00:21:00 AI and the future of software development* 00:26:42 Bret's approach to identifying customer needs and building AI companies* 00:32:09 The evolution of business models in the AI era* 00:41:00 The future of programming languages and software development* 00:49:38 Challenges in precisely communicating human intent to machines* 00:56:44 Discussion on Artificial General Intelligence (AGI) and its impact* 01:08:51 The future of agent-to-agent communication* 01:14:03 Bret's involvement in the OpenAI leadership crisis* 01:22:11 OpenAI's relationship with Microsoft* 01:23:23 OpenAI's mission and priorities* 01:27:40 Bret's guiding principles for career choices* 01:29:12 Brief discussion on pasta-making* 01:30:47 How Bret keeps up with AI developments* 01:32:15 Exciting research directions in AI* 01:35:19 Closing remarks and hiring at Sierra Transcript[00:02:05] Introduction and Guest Welcome[00:02:05] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host swyx, founder of smol.ai.[00:02:17] swyx: Hey, and today we're super excited to have Bret Taylor join us. Welcome. Thanks for having me. It's a little unreal to have you in the studio.[00:02:25] swyx: I've read about you so much over the years, like even before. Open AI effectively. I mean, I use Google Maps to get here. So like, thank you for everything that you've done. Like, like your story history, like, you know, I think people can find out what your greatest hits have been.[00:02:40] Bret Taylor's Early Career and Education[00:02:40] swyx: How do you usually like to introduce yourself when, you know, you talk about, you summarize your career, like, how do you look at yourself?[00:02:47] Bret: Yeah, it's a great question. You know, we, before we went on the mics here, we're talking about the audience for this podcast being more engineering. And I do think depending on the audience, I'll introduce myself differently because I've had a lot of [00:03:00] corporate and board roles. I probably self identify as an engineer more than anything else though.[00:03:04] Bret: So even when I was. Salesforce, I was coding on the weekends. So I think of myself as an engineer and then all the roles that I do in my career sort of start with that just because I do feel like engineering is sort of a mindset and how I approach most of my life. So I'm an engineer first and that's how I describe myself.[00:03:24] Bret: You majored in computer[00:03:25] swyx: science, like 1998. And, and I was high[00:03:28] Bret: school, actually my, my college degree was Oh, two undergrad. Oh, three masters. Right. That old.[00:03:33] swyx: Yeah. I mean, no, I was going, I was going like 1998 to 2003, but like engineering wasn't as, wasn't a thing back then. Like we didn't have the title of senior engineer, you know, kind of like, it was just.[00:03:44] swyx: You were a programmer, you were a developer, maybe. What was it like in Stanford? Like, what was that feeling like? You know, was it, were you feeling like on the cusp of a great computer revolution? Or was it just like a niche, you know, interest at the time?[00:03:57] Stanford and the Dot-Com Bubble[00:03:57] Bret: Well, I was at Stanford, as you said, from 1998 to [00:04:00] 2002.[00:04:02] Bret: 1998 was near the peak of the dot com bubble. So. This is back in the day where most people that they're coding in the computer lab, just because there was these sun microsystems, Unix boxes there that most of us had to do our assignments on. And every single day there was a. com like buying pizza for everybody.[00:04:20] Bret: I didn't have to like, I got. Free food, like my first two years of university and then the dot com bubble burst in the middle of my college career. And so by the end there was like tumbleweed going to the job fair, you know, it was like, cause it was hard to describe unless you were there at the time, the like level of hype and being a computer science major at Stanford was like, A thousand opportunities.[00:04:45] Bret: And then, and then when I left, it was like Microsoft, IBM.[00:04:49] Joining Google and Early Projects[00:04:49] Bret: And then the two startups that I applied to were VMware and Google. And I ended up going to Google in large part because a woman named Marissa Meyer, who had been a teaching [00:05:00] assistant when I was, what was called a section leader, which was like a junior teaching assistant kind of for one of the big interest.[00:05:05] Bret: Yes. Classes. She had gone there. And she was recruiting me and I knew her and it was sort of felt safe, you know, like, I don't know. I thought about it much, but it turned out to be a real blessing. I realized like, you know, you always want to think you'd pick Google if given the option, but no one knew at the time.[00:05:20] Bret: And I wonder if I'd graduated in like 1999 where I've been like, mom, I just got a job at pets. com. It's good. But you know, at the end I just didn't have any options. So I was like, do I want to go like make kernel software at VMware? Do I want to go build search at Google? And I chose Google. 50, 50 ball.[00:05:36] Bret: I'm not really a 50, 50 ball. So I feel very fortunate in retrospect that the economy collapsed because in some ways it forced me into like one of the greatest companies of all time, but I kind of lucked into it, I think.[00:05:47] The Google Maps Rewrite Story[00:05:47] Alessio: So the famous story about Google is that you rewrote the Google maps back in, in one week after the map quest quest maps acquisition, what was the story there?[00:05:57] Alessio: Is it. Actually true. Is it [00:06:00] being glorified? Like how, how did that come to be? And is there any detail that maybe Paul hasn't shared before?[00:06:06] Bret: It's largely true, but I'll give the color commentary. So it was actually the front end, not the back end, but it turns out for Google maps, the front end was sort of the hard part just because Google maps was.[00:06:17] Bret: Largely the first ish kind of really interactive web application, say first ish. I think Gmail certainly was though Gmail, probably a lot of people then who weren't engineers probably didn't appreciate its level of interactivity. It was just fast, but. Google maps, because you could drag the map and it was sort of graphical.[00:06:38] Bret: My, it really in the mainstream, I think, was it a map[00:06:41] swyx: quest back then that was, you had the arrows up and down, it[00:06:44] Bret: was up and down arrows. Each map was a single image and you just click left and then wait for a few seconds to the new map to let it was really small too, because generating a big image was kind of expensive on computers that day.[00:06:57] Bret: So Google maps was truly innovative in that [00:07:00] regard. The story on it. There was a small company called where two technologies started by two Danish brothers, Lars and Jens Rasmussen, who are two of my closest friends now. They had made a windows app called expedition, which had beautiful maps. Even in 2000.[00:07:18] Bret: For whenever we acquired or sort of acquired their company, Windows software was not particularly fashionable, but they were really passionate about mapping and we had made a local search product that was kind of middling in terms of popularity, sort of like a yellow page of search product. So we wanted to really go into mapping.[00:07:36] Bret: We'd started working on it. Their small team seemed passionate about it. So we're like, come join us. We can build this together.[00:07:42] Technical Challenges and Innovations[00:07:42] Bret: It turned out to be a great blessing that they had built a windows app because you're less technically constrained when you're doing native code than you are building a web browser, particularly back then when there weren't really interactive web apps and it ended up.[00:07:56] Bret: Changing the level of quality that we [00:08:00] wanted to hit with the app because we were shooting for something that felt like a native windows application. So it was a really good fortune that we sort of, you know, their unusual technical choices turned out to be the greatest blessing. So we spent a lot of time basically saying, how can you make a interactive draggable map in a web browser?[00:08:18] Bret: How do you progressively load, you know, new map tiles, you know, as you're dragging even things like down in the weeds of the browser at the time, most browsers like Internet Explorer, which was dominant at the time would only load two images at a time from the same domain. So we ended up making our map tile servers have like.[00:08:37] Bret: Forty different subdomains so we could load maps and parallels like lots of hacks. I'm happy to go into as much as like[00:08:44] swyx: HTTP connections and stuff.[00:08:46] Bret: They just like, there was just maximum parallelism of two. And so if you had a map, set of map tiles, like eight of them, so So we just, we were down in the weeds of the browser anyway.[00:08:56] Bret: So it was lots of plumbing. I can, I know a lot more about browsers than [00:09:00] most people, but then by the end of it, it was fairly, it was a lot of duct tape on that code. If you've ever done an engineering project where you're not really sure the path from point A to point B, it's almost like. Building a house by building one room at a time.[00:09:14] Bret: The, there's not a lot of architectural cohesion at the end. And then we acquired a company called Keyhole, which became Google earth, which was like that three, it was a native windows app as well, separate app, great app, but with that, we got licenses to all this satellite imagery. And so in August of 2005, we added.[00:09:33] Bret: Satellite imagery to Google Maps, which added even more complexity in the code base. And then we decided we wanted to support Safari. There was no mobile phones yet. So Safari was this like nascent browser on, on the Mac. And it turns out there's like a lot of decisions behind the scenes, sort of inspired by this windows app, like heavy use of XML and XSLT and all these like.[00:09:54] Bret: Technologies that were like briefly fashionable in the early two thousands and everyone hates now for good [00:10:00] reason. And it turns out that all of the XML functionality and Internet Explorer wasn't supporting Safari. So people are like re implementing like XML parsers. And it was just like this like pile of s**t.[00:10:11] Bret: And I had to say a s**t on your part. Yeah, of[00:10:12] Alessio: course.[00:10:13] Bret: So. It went from this like beautifully elegant application that everyone was proud of to something that probably had hundreds of K of JavaScript, which sounds like nothing. Now we're talking like people have modems, you know, not all modems, but it was a big deal.[00:10:29] Bret: So it was like slow. It took a while to load and just, it wasn't like a great code base. Like everything was fragile. So I just got. Super frustrated by it. And then one weekend I did rewrite all of it. And at the time the word JSON hadn't been coined yet too, just to give you a sense. So it's all XML.[00:10:47] swyx: Yeah.[00:10:47] Bret: So we used what is now you would call JSON, but I just said like, let's use eval so that we can parse the data fast. And, and again, that's, it would literally as JSON, but at the time there was no name for it. So we [00:11:00] just said, let's. Pass on JavaScript from the server and eval it. And then somebody just refactored the whole thing.[00:11:05] Bret: And, and it wasn't like I was some genius. It was just like, you know, if you knew everything you wished you had known at the beginning and I knew all the functionality, cause I was the primary, one of the primary authors of the JavaScript. And I just like, I just drank a lot of coffee and just stayed up all weekend.[00:11:22] Bret: And then I, I guess I developed a bit of reputation and no one knew about this for a long time. And then Paul who created Gmail and I ended up starting a company with him too, after all of this told this on a podcast and now it's large, but it's largely true. I did rewrite it and it, my proudest thing.[00:11:38] Bret: And I think JavaScript people appreciate this. Like the un G zipped bundle size for all of Google maps. When I rewrote, it was 20 K G zipped. It was like much smaller for the entire application. It went down by like 10 X. So. What happened on Google? Google is a pretty mainstream company. And so like our usage is shot up because it turns out like it's faster.[00:11:57] Bret: Just being faster is worth a lot of [00:12:00] percentage points of growth at a scale of Google. So how[00:12:03] swyx: much modern tooling did you have? Like test suites no compilers.[00:12:07] Bret: Actually, that's not true. We did it one thing. So I actually think Google, I, you can. Download it. There's a, Google has a closure compiler, a closure compiler.[00:12:15] Bret: I don't know if anyone still uses it. It's gone. Yeah. Yeah. It's sort of gone out of favor. Yeah. Well, even until recently it was better than most JavaScript minifiers because it was more like it did a lot more renaming of variables and things. Most people use ES build now just cause it's fast and closure compilers built on Java and super slow and stuff like that.[00:12:37] Bret: But, so we did have that, that was it. Okay.[00:12:39] The Evolution of Web Applications[00:12:39] Bret: So and that was treated internally, you know, it was a really interesting time at Google at the time because there's a lot of teams working on fairly advanced JavaScript when no one was. So Google suggest, which Kevin Gibbs was the tech lead for, was the first kind of type ahead, autocomplete, I believe in a web browser, and now it's just pervasive in search boxes that you sort of [00:13:00] see a type ahead there.[00:13:01] Bret: I mean, chat, dbt[00:13:01] swyx: just added it. It's kind of like a round trip.[00:13:03] Bret: Totally. No, it's now pervasive as a UI affordance, but that was like Kevin's 20 percent project. And then Gmail, Paul you know, he tells the story better than anyone, but he's like, you know, basically was scratching his own itch, but what was really neat about it is email, because it's such a productivity tool, just needed to be faster.[00:13:21] Bret: So, you know, he was scratching his own itch of just making more stuff work on the client side. And then we, because of Lars and Yen sort of like setting the bar of this windows app or like we need our maps to be draggable. So we ended up. Not only innovate in terms of having a big sync, what would be called a single page application today, but also all the graphical stuff you know, we were crashing Firefox, like it was going out of style because, you know, when you make a document object model with the idea that it's a document and then you layer on some JavaScript and then we're essentially abusing all of this, it just was running into code paths that were not.[00:13:56] Bret: Well, it's rotten, you know, at this time. And so it was [00:14:00] super fun. And, and, you know, in the building you had, so you had compilers, people helping minify JavaScript just practically, but there is a great engineering team. So they were like, that's why Closure Compiler is so good. It was like a. Person who actually knew about programming languages doing it, not just, you know, writing regular expressions.[00:14:17] Bret: And then the team that is now the Chrome team believe, and I, I don't know this for a fact, but I'm pretty sure Google is the main contributor to Firefox for a long time in terms of code. And a lot of browser people were there. So every time we would crash Firefox, we'd like walk up two floors and say like, what the hell is going on here?[00:14:35] Bret: And they would load their browser, like in a debugger. And we could like figure out exactly what was breaking. And you can't change the code, right? Cause it's the browser. It's like slow, right? I mean, slow to update. So, but we could figure out exactly where the bug was and then work around it in our JavaScript.[00:14:52] Bret: So it was just like new territory. Like so super, super fun time, just like a lot of, a lot of great engineers figuring out [00:15:00] new things. And And now, you know, the word, this term is no longer in fashion, but the word Ajax, which was asynchronous JavaScript and XML cause I'm telling you XML, but see the word XML there, to be fair, the way you made HTTP requests from a client to server was this.[00:15:18] Bret: Object called XML HTTP request because Microsoft and making Outlook web access back in the day made this and it turns out to have nothing to do with XML. It's just a way of making HTTP requests because XML was like the fashionable thing. It was like that was the way you, you know, you did it. But the JSON came out of that, you know, and then a lot of the best practices around building JavaScript applications is pre React.[00:15:44] Bret: I think React was probably the big conceptual step forward that we needed. Even my first social network after Google, we used a lot of like HTML injection and. Making real time updates was still very hand coded and it's really neat when you [00:16:00] see conceptual breakthroughs like react because it's, I just love those things where it's like obvious once you see it, but it's so not obvious until you do.[00:16:07] Bret: And actually, well, I'm sure we'll get into AI, but I, I sort of feel like we'll go through that evolution with AI agents as well that I feel like we're missing a lot of the core abstractions that I think in 10 years we'll be like, gosh, how'd you make agents? Before that, you know, but it was kind of that early days of web applications.[00:16:22] swyx: There's a lot of contenders for the reactive jobs of of AI, but no clear winner yet. I would say one thing I was there for, I mean, there's so much we can go into there. You just covered so much.[00:16:32] Product Management and Engineering Synergy[00:16:32] swyx: One thing I just, I just observe is that I think the early Google days had this interesting mix of PM and engineer, which I think you are, you didn't, you didn't wait for PM to tell you these are my, this is my PRD.[00:16:42] swyx: This is my requirements.[00:16:44] mix: Oh,[00:16:44] Bret: okay.[00:16:45] swyx: I wasn't technically a software engineer. I mean,[00:16:48] Bret: by title, obviously. Right, right, right.[00:16:51] swyx: It's like a blend. And I feel like these days, product is its own discipline and its own lore and own industry and engineering is its own thing. And there's this process [00:17:00] that happens and they're kind of separated, but you don't produce as good of a product as if they were the same person.[00:17:06] swyx: And I'm curious, you know, if, if that, if that sort of resonates in, in, in terms of like comparing early Google versus modern startups that you see out there,[00:17:16] Bret: I certainly like wear a lot of hats. So, you know, sort of biased in this, but I really agree that there's a lot of power and combining product design engineering into as few people as possible because, you know few great things have been created by committee, you know, and so.[00:17:33] Bret: If engineering is an order taking organization for product you can sometimes make meaningful things, but rarely will you create extremely well crafted breakthrough products. Those tend to be small teams who deeply understand the customer need that they're solving, who have a. Maniacal focus on outcomes.[00:17:53] Bret: And I think the reason why it's, I think for some areas, if you look at like software as a service five years ago, maybe you can have a [00:18:00] separation of product and engineering because most software as a service created five years ago. I wouldn't say there's like a lot of like. Technological breakthroughs required for most, you know, business applications.[00:18:11] Bret: And if you're making expense reporting software or whatever, it's useful. I don't mean to be dismissive of expense reporting software, but you probably just want to understand like, what are the requirements of the finance department? What are the requirements of an individual file expense report? Okay.[00:18:25] Bret: Go implement that. And you kind of know how web applications are implemented. You kind of know how to. How databases work, how to build auto scaling with your AWS cluster, whatever, you know, it's just, you're just applying best practices to yet another problem when you have areas like the early days of mobile development or the early days of interactive web applications, which I think Google Maps and Gmail represent, or now AI agents, you're in this constant conversation with what the requirements of your customers and stakeholders are and all the different people interacting with it.[00:18:58] Bret: And the capabilities of the [00:19:00] technology. And it's almost impossible to specify the requirements of a product when you're not sure of the limitations of the technology itself. And that's why I use the word conversation. It's not literal. That's sort of funny to use that word in the age of conversational AI.[00:19:15] Bret: You're constantly sort of saying, like, ideally, you could sprinkle some magic AI pixie dust and solve all the world's problems, but it's not the way it works. And it turns out that actually, I'll just give an interesting example.[00:19:26] AI Agents and Modern Tooling[00:19:26] Bret: I think most people listening probably use co pilots to code like Cursor or Devon or Microsoft Copilot or whatever.[00:19:34] Bret: Most of those tools are, they're remarkable. I'm, I couldn't, you know, imagine development without them now, but they're not autonomous yet. Like I wouldn't let it just write most code without my interactively inspecting it. We just are somewhere between it's an amazing co pilot and it's an autonomous software engineer.[00:19:53] Bret: As a product manager, like your aspirations for what the product is are like kind of meaningful. But [00:20:00] if you're a product person, yeah, of course you'd say it should be autonomous. You should click a button and program should come out the other side. The requirements meaningless. Like what matters is like, what is based on the like very nuanced limitations of the technology.[00:20:14] Bret: What is it capable of? And then how do you maximize the leverage? It gives a software engineering team, given those very nuanced trade offs. Coupled with the fact that those nuanced trade offs are changing more rapidly than any technology in my memory, meaning every few months you'll have new models with new capabilities.[00:20:34] Bret: So how do you construct a product that can absorb those new capabilities as rapidly as possible as well? That requires such a combination of technical depth and understanding the customer that you really need more integration. Of product design and engineering. And so I think it's why with these big technology waves, I think startups have a bit of a leg up relative to incumbents because they [00:21:00] tend to be sort of more self actualized in terms of just like bringing those disciplines closer together.[00:21:06] Bret: And in particular, I think entrepreneurs, the proverbial full stack engineers, you know, have a leg up as well because. I think most breakthroughs happen when you have someone who can understand those extremely nuanced technical trade offs, have a vision for a product. And then in the process of building it, have that, as I said, like metaphorical conversation with the technology, right?[00:21:30] Bret: Gosh, I ran into a technical limit that I didn't expect. It's not just like changing that feature. You might need to refactor the whole product based on that. And I think that's, that it's particularly important right now. So I don't, you know, if you, if you're building a big ERP system, probably there's a great reason to have product and engineering.[00:21:51] Bret: I think in general, the disciplines are there for a reason. I think when you're dealing with something as nuanced as the like technologies, like large language models today, there's a ton of [00:22:00] advantage of having. Individuals or organizations that integrate the disciplines more formally.[00:22:05] Alessio: That makes a lot of sense.[00:22:06] Alessio: I've run a lot of engineering teams in the past, and I think the product versus engineering tension has always been more about effort than like whether or not the feature is buildable. But I think, yeah, today you see a lot more of like. Models actually cannot do that. And I think the most interesting thing is on the startup side, people don't yet know where a lot of the AI value is going to accrue.[00:22:26] Alessio: So you have this rush of people building frameworks, building infrastructure, layered things, but we don't really know the shape of the compute. I'm curious that Sierra, like how you thought about building an house, a lot of the tooling for evals or like just, you know, building the agents and all of that.[00:22:41] Alessio: Versus how you see some of the startup opportunities that is maybe still out there.[00:22:46] Bret: We build most of our tooling in house at Sierra, not all. It's, we don't, it's not like not invented here syndrome necessarily, though, maybe slightly guilty of that in some ways, but because we're trying to build a platform [00:23:00] that's in Dorian, you know, we really want to have control over our own destiny.[00:23:03] Bret: And you had made a comment earlier that like. We're still trying to figure out who like the reactive agents are and the jury is still out. I would argue it hasn't been created yet. I don't think the jury is still out to go use that metaphor. We're sort of in the jQuery era of agents, not the react era.[00:23:19] Bret: And, and that's like a throwback for people listening,[00:23:22] swyx: we shouldn't rush it. You know?[00:23:23] Bret: No, yeah, that's my point is. And so. Because we're trying to create an enduring company at Sierra that outlives us, you know, I'm not sure we want to like attach our cart to some like to a horse where it's not clear that like we've figured out and I actually want as a company, we're trying to enable just at a high level and I'll, I'll quickly go back to tech at Sierra, we help consumer brands build customer facing AI agents.[00:23:48] Bret: So. Everyone from Sonos to ADT home security to Sirius XM, you know, if you call them on the phone and AI will pick up with you, you know, chat with them on the Sirius XM homepage. It's an AI agent called Harmony [00:24:00] that they've built on our platform. We're what are the contours of what it means for someone to build an end to end complete customer experience with AI with conversational AI.[00:24:09] Bret: You know, we really want to dive into the deep end of, of all the trade offs to do it. You know, where do you use fine tuning? Where do you string models together? You know, where do you use reasoning? Where do you use generation? How do you use reasoning? How do you express the guardrails of an agentic process?[00:24:25] Bret: How do you impose determinism on a fundamentally non deterministic technology? There's just a lot of really like as an important design space. And I could sit here and tell you, we have the best approach. Every entrepreneur will, you know. But I hope that in two years, we look back at our platform and laugh at how naive we were, because that's the pace of change broadly.[00:24:45] Bret: If you talk about like the startup opportunities, I'm not wholly skeptical of tools companies, but I'm fairly skeptical. There's always an exception for every role, but I believe that certainly there's a big market for [00:25:00] frontier models, but largely for companies with huge CapEx budgets. So. Open AI and Microsoft's Anthropic and Amazon Web Services, Google Cloud XAI, which is very well capitalized now, but I think the, the idea that a company can make money sort of pre training a foundation model is probably not true.[00:25:20] Bret: It's hard to, you're competing with just, you know, unreasonably large CapEx budgets. And I just like the cloud infrastructure market, I think will be largely there. I also really believe in the applications of AI. And I define that not as like building agents or things like that. I define it much more as like, you're actually solving a problem for a business.[00:25:40] Bret: So it's what Harvey is doing in legal profession or what cursor is doing for software engineering or what we're doing for customer experience and customer service. The reason I believe in that is I do think that in the age of AI, what's really interesting about software is it can actually complete a task.[00:25:56] Bret: It can actually do a job, which is very different than the value proposition of [00:26:00] software was to ancient history two years ago. And as a consequence, I think the way you build a solution and For a domain is very different than you would have before, which means that it's not obvious, like the incumbent incumbents have like a leg up, you know, necessarily, they certainly have some advantages, but there's just such a different form factor, you know, for providing a solution and it's just really valuable.[00:26:23] Bret: You know, it's. Like just think of how much money cursor is saving software engineering teams or the alternative, how much revenue it can produce tool making is really challenging. If you look at the cloud market, just as a analog, there are a lot of like interesting tools, companies, you know, Confluent, Monetized Kafka, Snowflake, Hortonworks, you know, there's a, there's a bunch of them.[00:26:48] Bret: A lot of them, you know, have that mix of sort of like like confluence or have the open source or open core or whatever you call it. I, I, I'm not an expert in this area. You know, I do think [00:27:00] that developers are fickle. I think that in the tool space, I probably like. Default towards open source being like the area that will win.[00:27:09] Bret: It's hard to build a company around this and then you end up with companies sort of built around open source to that can work. Don't get me wrong, but I just think that it's nowadays the tools are changing so rapidly that I'm like, not totally skeptical of tool makers, but I just think that open source will broadly win, but I think that the CapEx required for building frontier models is such that it will go to a handful of big companies.[00:27:33] Bret: And then I really believe in agents for specific domains which I think will, it's sort of the analog to software as a service in this new era. You know, it's like, if you just think of the cloud. You can lease a server. It's just a low level primitive, or you can buy an app like you know, Shopify or whatever.[00:27:51] Bret: And most people building a storefront would prefer Shopify over hand rolling their e commerce storefront. I think the same thing will be true of AI. So [00:28:00] I've. I tend to like, if I have a, like an entrepreneur asked me for advice, I'm like, you know, move up the stack as far as you can towards a customer need.[00:28:09] Bret: Broadly, but I, but it doesn't reduce my excitement about what is the reactive building agents kind of thing, just because it is, it is the right question to ask, but I think we'll probably play out probably an open source space more than anything else.[00:28:21] swyx: Yeah, and it's not a priority for you. There's a lot in there.[00:28:24] swyx: I'm kind of curious about your idea maze towards, there are many customer needs. You happen to identify customer experience as yours, but it could equally have been coding assistance or whatever. I think for some, I'm just kind of curious at the top down, how do you look at the world in terms of the potential problem space?[00:28:44] swyx: Because there are many people out there who are very smart and pick the wrong problem.[00:28:47] Bret: Yeah, that's a great question.[00:28:48] Future of Software Development[00:28:48] Bret: By the way, I would love to talk about the future of software, too, because despite the fact it didn't pick coding, I have a lot of that, but I can talk to I can answer your question, though, you know I think when a technology is as [00:29:00] cool as large language models.[00:29:02] Bret: You just see a lot of people starting from the technology and searching for a problem to solve. And I think it's why you see a lot of tools companies, because as a software engineer, you start building an app or a demo and you, you encounter some pain points. You're like,[00:29:17] swyx: a lot of[00:29:17] Bret: people are experiencing the same pain point.[00:29:19] Bret: What if I make it? That it's just very incremental. And you know, I always like to use the metaphor, like you can sell coffee beans, roasted coffee beans. You can add some value. You took coffee beans and you roasted them and roasted coffee beans largely, you know, are priced relative to the cost of the beans.[00:29:39] Bret: Or you can sell a latte and a latte. Is rarely priced directly like as a percentage of coffee bean prices. In fact, if you buy a latte at the airport, it's a captive audience. So it's a really expensive latte. And there's just a lot that goes into like. How much does a latte cost? And I bring it up because there's a supply chain from growing [00:30:00] coffee beans to roasting coffee beans to like, you know, you could make one at home or you could be in the airport and buy one and the margins of the company selling lattes in the airport is a lot higher than the, you know, people roasting the coffee beans and it's because you've actually solved a much more acute human problem in the airport.[00:30:19] Bret: And, and it's just worth a lot more to that person in that moment. It's kind of the way I think about technology too. It sounds funny to liken it to coffee beans, but you're selling tools on top of a large language model yet in some ways your market is big, but you're probably going to like be price compressed just because you're sort of a piece of infrastructure and then you have open source and all these other things competing with you naturally.[00:30:43] Bret: If you go and solve a really big business problem for somebody, that's actually like a meaningful business problem that AI facilitates, they will value it according to the value of that business problem. And so I actually feel like people should just stop. You're like, no, that's, that's [00:31:00] unfair. If you're searching for an idea of people, I, I love people trying things, even if, I mean, most of the, a lot of the greatest ideas have been things no one believed in.[00:31:07] Bret: So I like, if you're passionate about something, go do it. Like who am I to say, yeah, a hundred percent. Or Gmail, like Paul as far, I mean I, some of it's Laura at this point, but like Gmail is Paul's own email for a long time. , and then I amusingly and Paul can't correct me, I'm pretty sure he sent her in a link and like the first comment was like, this is really neat.[00:31:26] Bret: It would be great. It was not your email, but my own . I don't know if it's a true story. I'm pretty sure it's, yeah, I've read that before. So scratch your own niche. Fine. Like it depends on what your goal is. If you wanna do like a venture backed company, if its a. Passion project, f*****g passion, do it like don't listen to anybody.[00:31:41] Bret: In fact, but if you're trying to start, you know an enduring company, solve an important business problem. And I, and I do think that in the world of agents, the software industries has shifted where you're not just helping people more. People be more productive, but you're actually accomplishing tasks autonomously.[00:31:58] Bret: And as a consequence, I think the [00:32:00] addressable market has just greatly expanded just because software can actually do things now and actually accomplish tasks and how much is coding autocomplete worth. A fair amount. How much is the eventual, I'm certain we'll have it, the software agent that actually writes the code and delivers it to you, that's worth a lot.[00:32:20] Bret: And so, you know, I would just maybe look up from the large language models and start thinking about the economy and, you know, think from first principles. I don't wanna get too far afield, but just think about which parts of the economy. We'll benefit most from this intelligence and which parts can absorb it most easily.[00:32:38] Bret: And what would an agent in this space look like? Who's the customer of it is the technology feasible. And I would just start with these business problems more. And I think, you know, the best companies tend to have great engineers who happen to have great insight into a market. And it's that last part that I think some people.[00:32:56] Bret: Whether or not they have, it's like people start so much in the technology, they [00:33:00] lose the forest for the trees a little bit.[00:33:02] Alessio: How do you think about the model of still selling some sort of software versus selling more package labor? I feel like when people are selling the package labor, it's almost more stateless, you know, like it's easier to swap out if you're just putting an input and getting an output.[00:33:16] Alessio: If you think about coding, if there's no ID, you're just putting a prompt and getting back an app. It doesn't really matter. Who generates the app, you know, you have less of a buy in versus the platform you're building, I'm sure on the backend customers have to like put on their documentation and they have, you know, different workflows that they can tie in what's kind of like the line to draw there versus like going full where you're managed customer support team as a service outsource versus.[00:33:40] Alessio: This is the Sierra platform that you can build on. What was that decision? I'll sort of[00:33:44] Bret: like decouple the question in some ways, which is when you have something that's an agent, who is the person using it and what do they want to do with it? So let's just take your coding agent for a second. I will talk about Sierra as well.[00:33:59] Bret: Who's the [00:34:00] customer of a, an agent that actually produces software? Is it a software engineering manager? Is it a software engineer? And it's there, you know, intern so to speak. I don't know. I mean, we'll figure this out over the next few years. Like what is that? And is it generating code that you then review?[00:34:16] Bret: Is it generating code with a set of unit tests that pass, what is the actual. For lack of a better word contract, like, how do you know that it did what you wanted it to do? And then I would say like the product and the pricing, the packaging model sort of emerged from that. And I don't think the world's figured out.[00:34:33] Bret: I think it'll be different for every agent. You know, in our customer base, we do what's called outcome based pricing. So essentially every time the AI agent. Solves the problem or saves a customer or whatever it might be. There's a pre negotiated rate for that. We do that. Cause it's, we think that that's sort of the correct way agents, you know, should be packaged.[00:34:53] Bret: I look back at the history of like cloud software and notably the introduction of the browser, which led to [00:35:00] software being delivered in a browser, like Salesforce to. Famously invented sort of software as a service, which is both a technical delivery model through the browser, but also a business model, which is you subscribe to it rather than pay for a perpetual license.[00:35:13] Bret: Those two things are somewhat orthogonal, but not really. If you think about the idea of software running in a browser, that's hosted. Data center that you don't own, you sort of needed to change the business model because you don't, you can't really buy a perpetual license or something otherwise like, how do you afford making changes to it?[00:35:31] Bret: So it only worked when you were buying like a new version every year or whatever. So to some degree, but then the business model shift actually changed business as we know it, because now like. Things like Adobe Photoshop. Now you subscribe to rather than purchase. So it ended up where you had a technical shift and a business model shift that were very logically intertwined that actually the business model shift was turned out to be as significant as the technical as the shift.[00:35:59] Bret: And I think with [00:36:00] agents, because they actually accomplish a job, I do think that it doesn't make sense to me that you'd pay for the privilege of like. Using the software like that coding agent, like if it writes really bad code, like fire it, you know, I don't know what the right metaphor is like you should pay for a job.[00:36:17] Bret: Well done in my opinion. I mean, that's how you pay your software engineers, right? And[00:36:20] swyx: and well, not really. We paid to put them on salary and give them options and they vest over time. That's fair.[00:36:26] Bret: But my point is that you don't pay them for how many characters they write, which is sort of the token based, you know, whatever, like, There's a, that famous Apple story where we're like asking for a report of how many lines of code you wrote.[00:36:40] Bret: And one of the engineers showed up with like a negative number cause he had just like done a big refactoring. There was like a big F you to management who didn't understand how software is written. You know, my sense is like the traditional usage based or seat based thing. It's just going to look really antiquated.[00:36:55] Bret: Cause it's like asking your software engineer, how many lines of code did you write today? Like who cares? Like, cause [00:37:00] absolutely no correlation. So my old view is I don't think it's be different in every category, but I do think that that is the, if an agent is doing a job, you should, I think it properly incentivizes the maker of that agent and the customer of, of your pain for the job well done.[00:37:16] Bret: It's not always perfect to measure. It's hard to measure engineering productivity, but you can, you should do something other than how many keys you typed, you know Talk about perverse incentives for AI, right? Like I can write really long functions to do the same thing, right? So broadly speaking, you know, I do think that we're going to see a change in business models of software towards outcomes.[00:37:36] Bret: And I think you'll see a change in delivery models too. And, and, you know, in our customer base you know, we empower our customers to really have their hands on the steering wheel of what the agent does they, they want and need that. But the role is different. You know, at a lot of our customers, the customer experience operations folks have renamed themselves the AI architects, which I think is really cool.[00:37:55] Bret: And, you know, it's like in the early days of the Internet, there's the role of the webmaster. [00:38:00] And I don't know whether your webmaster is not a fashionable, you know, Term, nor is it a job anymore? I just, I don't know. Will they, our tech stand the test of time? Maybe, maybe not. But I do think that again, I like, you know, because everyone listening right now is a software engineer.[00:38:14] Bret: Like what is the form factor of a coding agent? And actually I'll, I'll take a breath. Cause actually I have a bunch of pins on them. Like I wrote a blog post right before Christmas, just on the future of software development. And one of the things that's interesting is like, if you look at the way I use cursor today, as an example, it's inside of.[00:38:31] Bret: A repackaged visual studio code environment. I sometimes use the sort of agentic parts of it, but it's largely, you know, I've sort of gotten a good routine of making it auto complete code in the way I want through tuning it properly when it actually can write. I do wonder what like the future of development environments will look like.[00:38:55] Bret: And to your point on what is a software product, I think it's going to change a lot in [00:39:00] ways that will surprise us. But I always use, I use the metaphor in my blog post of, have you all driven around in a way, Mo around here? Yeah, everyone has. And there are these Jaguars, the really nice cars, but it's funny because it still has a steering wheel, even though there's no one sitting there and the steering wheels like turning and stuff clearly in the future.[00:39:16] Bret: If once we get to that, be more ubiquitous, like why have the steering wheel and also why have all the seats facing forward? Maybe just for car sickness. I don't know, but you could totally rearrange the car. I mean, so much of the car is oriented around the driver, so. It stands to reason to me that like, well, autonomous agents for software engineering run through visual studio code.[00:39:37] Bret: That seems a little bit silly because having a single source code file open one at a time is kind of a goofy form factor for when like the code isn't being written primarily by you, but it begs the question of what's your relationship with that agent. And I think the same is true in our industry of customer experience, which is like.[00:39:55] Bret: Who are the people managing this agent? What are the tools do they need? And they definitely need [00:40:00] tools, but it's probably pretty different than the tools we had before. It's certainly different than training a contact center team. And as software engineers, I think that I would like to see particularly like on the passion project side or research side.[00:40:14] Bret: More innovation in programming languages. I think that we're bringing the cost of writing code down to zero. So the fact that we're still writing Python with AI cracks me up just cause it's like literally was designed to be ergonomic to write, not safe to run or fast to run. I would love to see more innovation and how we verify program correctness.[00:40:37] Bret: I studied for formal verification in college a little bit and. It's not very fashionable because it's really like tedious and slow and doesn't work very well. If a lot of code is being written by a machine, you know, one of the primary values we can provide is verifying that it actually does what we intend that it does.[00:40:56] Bret: I think there should be lots of interesting things in the software development life cycle, like how [00:41:00] we think of testing and everything else, because. If you think about if we have to manually read every line of code that's coming out as machines, it will just rate limit how much the machines can do. The alternative is totally unsafe.[00:41:13] Bret: So I wouldn't want to put code in production that didn't go through proper code review and inspection. So my whole view is like, I actually think there's like an AI native I don't think the coding agents don't work well enough to do this yet, but once they do, what is sort of an AI native software development life cycle and how do you actually.[00:41:31] Bret: Enable the creators of software to produce the highest quality, most robust, fastest software and know that it's correct. And I think that's an incredible opportunity. I mean, how much C code can we rewrite and rust and make it safe so that there's fewer security vulnerabilities. Can we like have more efficient, safer code than ever before?[00:41:53] Bret: And can you have someone who's like that guy in the matrix, you know, like staring at the little green things, like where could you have an operator [00:42:00] of a code generating machine be like superhuman? I think that's a cool vision. And I think too many people are focused on like. Autocomplete, you know, right now, I'm not, I'm not even, I'm guilty as charged.[00:42:10] Bret: I guess in some ways, but I just like, I'd like to see some bolder ideas. And that's why when you were joking, you know, talking about what's the react of whatever, I think we're clearly in a local maximum, you know, metaphor, like sort of conceptual local maximum, obviously it's moving really fast. I think we're moving out of it.[00:42:26] Alessio: Yeah. At the end of 23, I've read this blog post from syntax to semantics. Like if you think about Python. It's taking C and making it more semantic and LLMs are like the ultimate semantic program, right? You can just talk to them and they can generate any type of syntax from your language. But again, the languages that they have to use were made for us, not for them.[00:42:46] Alessio: But the problem is like, as long as you will ever need a human to intervene, you cannot change the language under it. You know what I mean? So I'm curious at what point of automation we'll need to get, we're going to be okay making changes. To the underlying languages, [00:43:00] like the programming languages versus just saying, Hey, you just got to write Python because I understand Python and I'm more important at the end of the day than the model.[00:43:08] Alessio: But I think that will change, but I don't know if it's like two years or five years. I think it's more nuanced actually.[00:43:13] Bret: So I think there's a, some of the more interesting programming languages bring semantics into syntax. So let me, that's a little reductive, but like Rust as an example, Rust is memory safe.[00:43:25] Bret: Statically, and that was a really interesting conceptual, but it's why it's hard to write rust. It's why most people write python instead of rust. I think rust programs are safer and faster than python, probably slower to compile. But like broadly speaking, like given the option, if you didn't have to care about the labor that went into it.[00:43:45] Bret: You should prefer a program written in Rust over a program written in Python, just because it will run more efficiently. It's almost certainly safer, et cetera, et cetera, depending on how you define safe, but most people don't write Rust because it's kind of a pain in the ass. And [00:44:00] the audience of people who can is smaller, but it's sort of better in most, most ways.[00:44:05] Bret: And again, let's say you're making a web service and you didn't have to care about how hard it was to write. If you just got the output of the web service, the rest one would be cheaper to operate. It's certainly cheaper and probably more correct just because there's so much in the static analysis implied by the rest programming language that it probably will have fewer runtime errors and things like that as well.[00:44:25] Bret: So I just give that as an example, because so rust, at least my understanding that came out of the Mozilla team, because. There's lots of security vulnerabilities in the browser and it needs to be really fast. They said, okay, we want to put more of a burden at the authorship time to have fewer issues at runtime.[00:44:43] Bret: And we need the constraint that it has to be done statically because browsers need to be really fast. My sense is if you just think about like the, the needs of a programming language today, where the role of a software engineer is [00:45:00] to use an AI to generate functionality and audit that it does in fact work as intended, maybe functionally, maybe from like a correctness standpoint, some combination thereof, how would you create a programming system that facilitated that?[00:45:15] Bret: And, you know, I bring up Rust is because I think it's a good example of like, I think given a choice of writing in C or Rust, you should choose Rust today. I think most people would say that, even C aficionados, just because. C is largely less safe for very similar, you know, trade offs, you know, for the, the system and now with AI, it's like, okay, well, that just changes the game on writing these things.[00:45:36] Bret: And so like, I just wonder if a combination of programming languages that are more structurally oriented towards the values that we need from an AI generated program, verifiable correctness and all of that. If it's tedious to produce for a person, that maybe doesn't matter. But one thing, like if I asked you, is this rest program memory safe?[00:45:58] Bret: You wouldn't have to read it, you just have [00:46:00] to compile it. So that's interesting. I mean, that's like an, that's one example of a very modest form of formal verification. So I bring that up because I do think you have AI inspect AI, you can have AI reviewed. Do AI code reviews. It would disappoint me if the best we could get was AI reviewing Python and having scaled a few very large.[00:46:21] Bret: Websites that were written on Python. It's just like, you know, expensive and it's like every, trust me, every team who's written a big web service in Python has experimented with like Pi Pi and all these things just to make it slightly more efficient than it naturally is. You don't really have true multi threading anyway.[00:46:36] Bret: It's just like clearly that you do it just because it's convenient to write. And I just feel like we're, I don't want to say it's insane. I just mean. I do think we're at a local maximum. And I would hope that we create a programming system, a combination of programming languages, formal verification, testing, automated code reviews, where you can use AI to generate software in a high scale way and trust it.[00:46:59] Bret: And you're [00:47:00] not limited by your ability to read it necessarily. I don't know exactly what form that would take, but I feel like that would be a pretty cool world to live in.[00:47:08] Alessio: Yeah. We had Chris Lanner on the podcast. He's doing great work with modular. I mean, I love. LVM. Yeah. Basically merging rust in and Python.[00:47:15] Alessio: That's kind of the idea. Should be, but I'm curious is like, for them a big use case was like making it compatible with Python, same APIs so that Python developers could use it. Yeah. And so I, I wonder at what point, well, yeah.[00:47:26] Bret: At least my understanding is they're targeting the data science Yeah. Machine learning crowd, which is all written in Python, so still feels like a local maximum.[00:47:34] Bret: Yeah.[00:47:34] swyx: Yeah, exactly. I'll force you to make a prediction. You know, Python's roughly 30 years old. In 30 years from now, is Rust going to be bigger than Python?[00:47:42] Bret: I don't know this, but just, I don't even know this is a prediction. I just am sort of like saying stuff I hope is true. I would like to see an AI native programming language and programming system, and I use language because I'm not sure language is even the right thing, but I hope in 30 years, there's an AI native way we make [00:48:00] software that is wholly uncorrelated with the current set of programming languages.[00:48:04] Bret: or not uncorrelated, but I think most programming languages today were designed to be efficiently authored by people and some have different trade offs.[00:48:15] Evolution of Programming Languages[00:48:15] Bret: You know, you have Haskell and others that were designed for abstractions for parallelism and things like that. You have programming languages like Python, which are designed to be very easily written, sort of like Perl and Python lineage, which is why data scientists use it.[00:48:31] Bret: It's it can, it has a. Interactive mode, things like that. And I love, I'm a huge Python fan. So despite all my Python trash talk, a huge Python fan wrote at least two of my three companies were exclusively written in Python and then C came out of the birth of Unix and it wasn't the first, but certainly the most prominent first step after assembly language, right?[00:48:54] Bret: Where you had higher level abstractions rather than and going beyond go to, to like abstractions, [00:49:00] like the for loop and the while loop.[00:49:01] The Future of Software Engineering[00:49:01] Bret: So I just think that if the act of writing code is no longer a meaningful human exercise, maybe it will be, I don't know. I'm just saying it sort of feels like maybe it's one of those parts of history that just will sort of like go away, but there's still the role of this offer engineer, like the person actually building the system.[00:49:20] Bret: Right. And. What does a programming system for that form factor look like?[00:49:25] React and Front-End Development[00:49:25] Bret: And I, I just have a, I hope to be just like I mentioned, I remember I was at Facebook in the very early days when, when, what is now react was being created. And I remember when the, it was like released open source I had left by that time and I was just like, this is so f*****g cool.[00:49:42] Bret: Like, you know, to basically model your app independent of the data flowing through it, just made everything easier. And then now. You know, I can create, like there's a lot of the front end software gym play is like a little chaotic for me, to be honest with you. It is like, it's sort of like [00:50:00] abstraction soup right now for me, but like some of those core ideas felt really ergonomic.[00:50:04] Bret: I just wanna, I'm just looking forward to the day when someone comes up with a programming system that feels both really like an aha moment, but completely foreign to me at the same time. Because they created it with sort of like from first principles recognizing that like. Authoring code in an editor is maybe not like the primary like reason why a programming system exists anymore.[00:50:26] Bret: And I think that's like, that would be a very exciting day for me.[00:50:28] The Role of AI in Programming[00:50:28] swyx: Yeah, I would say like the various versions of this discussion have happened at the end of the day, you still need to precisely communicate what you want. As a manager of people, as someone who has done many, many legal contracts, you know how hard that is.[00:50:42] swyx: And then now we have to talk to machines doing that and AIs interpreting what we mean and reading our minds effectively. I don't know how to get across that barrier of translating human intent to instructions. And yes, it can be more declarative, but I don't know if it'll ever Crossover from being [00:51:00] a programming language to something more than that.[00:51:02] Bret: I agree with you. And I actually do think if you look at like a legal contract, you know, the imprecision of the English language, it's like a flaw in the system. How many[00:51:12] swyx: holes there are.[00:51:13] Bret: And I do think that when you're making a mission critical software system, I don't think it should be English language prompts.[00:51:19] Bret: I think that is silly because you want the precision of a a programming language. My point was less about that and more about if the actual act of authoring it, like if you.[00:51:32] Formal Verification in Software[00:51:32] Bret: I'll think of some embedded systems do use formal verification. I know it's very common in like security protocols now so that you can, because the importance of correctness is so great.[00:51:41] Bret: My intellectual exercise is like, why not do that for all software? I mean, probably that's silly just literally to do what we literally do for. These low level security protocols, but the only reason we don't is because it's hard and tedious and hard and tedious are no longer factors. So, like, if I could, I mean, [00:52:00] just think of, like, the silliest app on your phone right now, the idea that that app should be, like, formally verified for its correctness feels laughable right now because, like, God, why would you spend the time on it?[00:52:10] Bret: But if it's zero costs, like, yeah, I guess so. I mean, it never crashed. That's probably good. You know, why not? I just want to, like, set our bars really high. Like. We should make, software has been amazing. Like there's a Mark Andreessen blog post, software is eating the world. And you know, our whole life is, is mediated digitally.[00:52:26] Bret: And that's just increasing with AI. And now we'll have our personal agents talking to the agents on the CRO platform and it's agents all the way down, you know, our core infrastructure is running on these digital systems. We now have like, and we've had a shortage of software developers for my entire life.[00:52:45] Bret: And as a consequence, you know if you look, remember like health care, got healthcare. gov that fiasco security vulnerabilities leading to state actors getting access to critical infrastructure. I'm like. We now have like created this like amazing system that can [00:53:00] like, we can fix this, you know, and I, I just want to, I'm both excited about the productivity gains in the economy, but I just think as software engineers, we should be bolder.[00:53:08] Bret: Like we should have aspirations to fix these systems so that like in general, as you said, as precise as we want to be in the specification of the system. We can make it work correctly now, and I'm being a little bit hand wavy, and I think we need some systems. I think that's where we should set the bar, especially when so much of our life depends on this critical digital infrastructure.[00:53:28] Bret: So I'm I'm just like super optimistic about it. But actually, let's go to w

Tell us what you think about this podcast!In this series, Bishop Rader Johnson emphasizes the qualities God seeks in His faithful servants: availability and reliability. He explains that the best dependability comes from making ourselves available to God. Whatever role we desire to fulfill in the church, God will equip us with the ability to do it if we remain available and reliable.  We are cautioned against becoming too absorbed in the busyness of life, reminding us that our devotion should always prioritize the Lord. Tune in for encouragement and practical insights on living a life of faithful service to God.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson begins with the foundation scripture in Matthew 16:24-28, teaching that surrendering our lives to God is key to living a spiritual life. Denying ourselves, taking up our cross, and committing to God's will allows us to align with His thoughts, character, and actions. God desires us to reflect His nature and, through surrender, fulfill our spiritual purpose while securing eternal life. Tune in to find out how you can embrace the surrendered life God calls us to live.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

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Tell us what you think about this podcast!In this series, Bishop Rader Johnson begins with the foundation scripture in Matthew 16:24-28, teaching that surrendering our lives to God is key to living a spiritual life. Denying ourselves, taking up our cross, and committing to God's will allows us to align with His thoughts, character, and actions. God desires us to reflect His nature and, through surrender, fulfill our spiritual purpose while securing eternal life. Tune in to find out how you can embrace the surrendered life God calls us to live.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson begins with the foundation scripture in Matthew 16:24-28, teaching that surrendering our lives to God is key to living a spiritual life. Denying ourselves, taking up our cross, and committing to God's will allows us to align with His thoughts, character, and actions. God desires us to reflect His nature and, through surrender, fulfill our spiritual purpose while securing eternal life. Tune in to find out how you can embrace the surrendered life God calls us to live.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!In this series, Bishop Rader Johnson begins with the foundation scripture in Matthew 16:24-28, teaching that surrendering our lives to God is key to living a spiritual life. Denying ourselves, taking up our cross, and committing to God's will allows us to align with His thoughts, character, and actions. God desires us to reflect His nature and, through surrender, fulfill our spiritual purpose while securing eternal life. Tune in to find out how you can embrace the surrendered life God calls us to live.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Applications close Monday for the NYC AI Engineer Summit focusing on AI Leadership and Agent Engineering! If you applied, invites should be rolling out shortly.The search landscape is experiencing a fundamental shift. Google built a >$2T company with the “10 blue links” experience, driven by PageRank as the core innovation for ranking. This was a big improvement from the previous directory-based experiences of AltaVista and Yahoo. Almost 4 decades later, Google is now stuck in this links-based experience, especially from a business model perspective. This legacy architecture creates fundamental constraints:* Must return results in ~400 milliseconds* Required to maintain comprehensive web coverage* Tied to keyword-based matching algorithms* Cost structures optimized for traditional indexingAs we move from the era of links to the era of answers, the way search works is changing. You're not showing a user links, but the goal is to provide context to an LLM. This means moving from keyword based search to more semantic understanding of the content:The link prediction objective can be seen as like a neural PageRank because what you're doing is you're predicting the links people share... but it's more powerful than PageRank. It's strictly more powerful because people might refer to that Paul Graham fundraising essay in like a thousand different ways. And so our model learns all the different ways.All of this is now powered by a $5M cluster with 144 H200s:This architectural choice enables entirely new search capabilities:* Comprehensive result sets instead of approximations* Deep semantic understanding of queries* Ability to process complex, natural language requestsAs search becomes more complex, time to results becomes a variable:People think of searches as like, oh, it takes 500 milliseconds because we've been conditioned... But what if searches can take like a minute or 10 minutes or a whole day, what can you then do?Unlike traditional search engines' fixed-cost indexing, Exa employs a hybrid approach:* Front-loaded compute for indexing and embeddings* Variable inference costs based on query complexity* Mix of owned infrastructure ($5M H200 cluster) and cloud resourcesExa sees a lot of competition from products like Perplexity and ChatGPT Search which layer AI on top of traditional search backends, but Exa is betting that true innovation requires rethinking search from the ground up. For example, the recently launched Websets, a way to turn searches into structured output in grid format, allowing you to create lists and databases out of web pages. The company raised a $17M Series A to build towards this mission, so keep an eye out for them in 2025. Chapters* 00:00:00 Introductions* 00:01:12 ExaAI's initial pitch and concept* 00:02:33 Will's background at SpaceX and Zoox* 00:03:45 Evolution of ExaAI (formerly Metaphor Systems)* 00:05:38 Exa's link prediction technology* 00:09:20 Meaning of the name "Exa"* 00:10:36 ExaAI's new product launch and capabilities* 00:13:33 Compute budgets and variable compute products* 00:14:43 Websets as a B2B offering* 00:19:28 How do you build a search engine?* 00:22:43 What is Neural PageRank?* 00:27:58 Exa use cases * 00:35:00 Auto-prompting* 00:38:42 Building agentic search* 00:44:19 Is o1 on the path to AGI?* 00:49:59 Company culture and nap pods* 00:54:52 Economics of AI search and the future of search technologyFull YouTube TranscriptPlease like and subscribe!Show Notes* ExaAI* Web Search Product* Websets* Series A Announcement* Exa Nap Pods* Perplexity AI* Character.AITranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:10]: Hey, and today we're in the studio with my good friend and former landlord, Will Bryk. Roommate. How you doing? Will, you're now CEO co-founder of ExaAI, used to be Metaphor Systems. What's your background, your story?Will [00:00:30]: Yeah, sure. So, yeah, I'm CEO of Exa. I've been doing it for three years. I guess I've always been interested in search, whether I knew it or not. Like, since I was a kid, I've always been interested in, like, high-quality information. And, like, you know, even in high school, wanted to improve the way we get information from news. And then in college, built a mini search engine. And then with Exa, like, you know, it's kind of like fulfilling the dream of actually being able to solve all the information needs I wanted as a kid. Yeah, I guess. I would say my entire life has kind of been rotating around this problem, which is pretty cool. Yeah.Swyx [00:00:50]: What'd you enter YC with?Will [00:00:53]: We entered YC with, uh, we are better than Google. Like, Google 2.0.Swyx [00:01:12]: What makes you say that? Like, that's so audacious to come out of the box with.Will [00:01:16]: Yeah, okay, so you have to remember the time. This was summer 2021. And, uh, GPT-3 had come out. Like, here was this magical thing that you could talk to, you could enter a whole paragraph, and it understands what you mean, understands the subtlety of your language. And then there was Google. Uh, which felt like it hadn't changed in a decade, uh, because it really hadn't. And it, like, you would give it a simple query, like, I don't know, uh, shirts without stripes, and it would give you a bunch of results for the shirts with stripes. And so, like, Google could barely understand you, and GBD3 could. And the theory was, what if you could make a search engine that actually understood you? What if you could apply the insights from LLMs to a search engine? And it's really been the same idea ever since. And we're actually a lot closer now, uh, to doing that. Yeah.Alessio [00:01:55]: Did you have any trouble making people believe? Obviously, there's the same element. I mean, YC overlap, was YC pretty AI forward, even 2021, or?Will [00:02:03]: It's nothing like it is today. But, um, uh, there were a few AI companies, but, uh, we were definitely, like, bold. And I think people, VCs generally like boldness, and we definitely had some AI background, and we had a working demo. So there was evidence that we could build something that was going to work. But yeah, I think, like, the fundamentals were there. I think people at the time were talking about how, you know, Google was failing in a lot of ways. And so there was a bit of conversation about it, but AI was not a big, big thing at the time. Yeah. Yeah.Alessio [00:02:33]: Before we jump into Exa, any fun background stories? I know you interned at SpaceX, any Elon, uh, stories? I know you were at Zoox as well, you know, kind of like robotics at Harvard. Any stuff that you saw early that you thought was going to get solved that maybe it's not solved today?Will [00:02:48]: Oh yeah. I mean, lots of things like that. Like, uh, I never really learned how to drive because I believed Elon that self-driving cars would happen. It did happen. And I take them every night to get home. But it took like 10 more years than I thought. Do you still not know how to drive? I know how to drive now. I learned it like two years ago. That would have been great to like, just, you know, Yeah, yeah, yeah. You know? Um, I was obsessed with Elon. Yeah. I mean, I worked at SpaceX because I really just wanted to work at one of his companies. And I remember they had a rule, like interns cannot touch Elon. And, um, that rule actually influenced my actions.Swyx [00:03:18]: Is it, can Elon touch interns? Ooh, like physically?Will [00:03:22]: Or like talk? Physically, physically, yeah, yeah, yeah, yeah. Okay, interesting. He's changed a lot, but, um, I mean, his companies are amazing. Um,Swyx [00:03:28]: What if you beat him at Diablo 2, Diablo 4, you know, like, Ah, maybe.Alessio [00:03:34]: I want to jump into, I know there's a lot of backstory used to be called metaphor system. So, um, and it, you've always been kind of like a prominent company, maybe at least RAI circles in the NSF.Swyx [00:03:45]: I'm actually curious how Metaphor got its initial aura. You launched with like, very little. We launched very little. Like there was, there was this like big splash image of like, this is Aurora or something. Yeah. Right. And then I was like, okay, what this thing, like the vibes are good, but I don't know what it is. And I think, I think it was much more sort of maybe consumer facing than what you are today. Would you say that's true?Will [00:04:06]: No, it's always been about building a better search algorithm, like search, like, just like the vision has always been perfect search. And if you do that, uh, we will figure out the downstream use cases later. It started on this fundamental belief that you could have perfect search over the web and we could talk about what that means. And like the initial thing we released was really just like our first search engine, like trying to get it out there. Kind of like, you know, an open source. So when OpenAI released, uh, ChachBt, like they didn't, I don't know how, how much of a game plan they had. They kind of just wanted to get something out there.Swyx [00:04:33]: Spooky research preview.Will [00:04:34]: Yeah, exactly. And it kind of morphed from a research company to a product company at that point. And I think similarly for us, like we were research, we started as a research endeavor with a, you know, clear eyes that like, if we succeed, it will be a massive business to make out of it. And that's kind of basically what happened. I think there are actually a lot of parallels to, of w between Exa and OpenAI. I often say we're the OpenAI of search. Um, because. Because we're a research company, we're a research startup that does like fundamental research into, uh, making like AGI for search in a, in a way. Uh, and then we have all these like, uh, business products that come out of that.Swyx [00:05:08]: Interesting. I want to ask a little bit more about Metaforesight and then we can go full Exa. When I first met you, which was really funny, cause like literally I stayed in your house in a very historic, uh, Hayes, Hayes Valley place. You said you were building sort of like link prediction foundation model, and I think there's still a lot of foundation model work. I mean, within Exa today, but what does that even mean? I cannot be the only person confused by that because like there's a limited vocabulary or tokens you're telling me, like the tokens are the links or, you know, like it's not, it's not clear. Yeah.Will [00:05:38]: Uh, what we meant by link prediction is that you are literally predicting, like given some texts, you're predicting the links that follow. Yes. That refers to like, it's how we describe the training procedure, which is that we find links on the web. Uh, we take the text surrounding the link. And then we predict. Which link follows you, like, uh, you know, similar to transformers where, uh, you're trying to predict the next token here, you're trying to predict the next link. And so you kind of like hide the link from the transformer. So if someone writes, you know, imagine some article where someone says, Hey, check out this really cool aerospace startup. And they, they say spacex.com afterwards, uh, we hide the spacex.com and ask the model, like what link came next. And by doing that many, many times, you know, billions of times, you could actually build a search engine out of that because then, uh, at query time at search time. Uh, you type in, uh, a query that's like really cool aerospace startup and the model will then try to predict what are the most likely links. So there's a lot of analogs to transformers, but like to actually make this work, it does require like a different architecture than, but it's transformer inspired. Yeah.Alessio [00:06:41]: What's the design decision between doing that versus extracting the link and the description and then embedding the description and then using, um, yeah. What do you need to predict the URL versus like just describing, because you're kind of do a similar thing in a way. Right. It's kind of like based on this description, it was like the closest link for it. So one thing is like predicting the link. The other approach is like I extract the link and the description, and then based on the query, I searched the closest description to it more. Yeah.Will [00:07:09]: That, that, by the way, that is, that is the link refers here to a document. It's not, I think one confusing thing is it's not, you're not actually predicting the URL, the URL itself that would require like the, the system to have memorized URLs. You're actually like getting the actual document, a more accurate name could be document prediction. I see. This was the initial like base model that Exo was trained on, but we've moved beyond that similar to like how, you know, uh, to train a really good like language model, you might start with this like self-supervised objective of predicting the next token and then, uh, just from random stuff on the web. But then you, you want to, uh, add a bunch of like synthetic data and like supervised fine tuning, um, stuff like that to make it really like controllable and robust. Yeah.Alessio [00:07:48]: Yeah. We just have flow from Lindy and, uh, their Lindy started to like hallucinate recrolling YouTube links instead of like, uh, something. Yeah. Support guide. So. Oh, interesting. Yeah.Swyx [00:07:57]: So round about January, you announced your series A and renamed to Exo. I didn't like the name at the, at the initial, but it's grown on me. I liked metaphor, but apparently people can spell metaphor. What would you say are the major components of Exo today? Right? Like, I feel like it used to be very model heavy. Then at the AI engineer conference, Shreyas gave a really good talk on the vector database that you guys have. What are the other major moving parts of Exo? Okay.Will [00:08:23]: So Exo overall is a search engine. Yeah. We're trying to make it like a perfect search engine. And to do that, you have to build lots of, and we're doing it from scratch, right? So to do that, you have to build lots of different. The crawler. Yeah. You have to crawl a bunch of the web. First of all, you have to find the URLs to crawl. Uh, it's connected to the crawler, but yeah, you find URLs, you crawl those URLs. Then you have to process them with some, you know, it could be an embedding model. It could be something more complex, but you need to take, you know, or like, you know, in the past it was like a keyword inverted index. Like you would process all these documents you gather into some processed index, and then you have to serve that. Uh, you had high throughput at low latency. And so that, and that's like the vector database. And so it's like the crawling system, the AI processing system, and then the serving system. Those are all like, you know, teams of like hundreds, maybe thousands of people at Google. Um, but for us, it's like one or two people each typically, but yeah.Alessio [00:09:13]: Can you explain the meaning of, uh, Exo, just the story 10 to the 16th, uh, 18, 18.Will [00:09:20]: Yeah, yeah, yeah, sure. So. Exo means 10 to the 18th, which is in stark contrast to. To Google, which is 10 to the hundredth. Uh, we actually have these like awesome shirts that are like 10th to 18th is greater than 10th to the hundredth. Yeah, it's great. And it's great because it's provocative. It's like every engineer in Silicon Valley is like, what? No, it's not true. Um, like, yeah. And, uh, and then you, you ask them, okay, what does it actually mean? And like the creative ones will, will recognize it. But yeah, I mean, 10 to the 18th is better than 10 to the hundredth when it comes to search, because with search, you want like the actual list of, of things that match what you're asking for. You don't want like the whole web. You want to basically with search filter, the, like everything that humanity has ever created to exactly what you want. And so the idea is like smaller is better there. You want like the best 10th to the 18th and not the 10th to the hundredth. I'm like, one way to say this is like, you know how Google often says at the top, uh, like, you know, 30 million results found. And it's like crazy. Cause you're looking for like the first startups in San Francisco that work on hardware or something. And like, they're not 30 million results like that. What you want is like 325 results found. And those are all the results. That's what you really want with search. And that's, that's our vision. It's like, it just gives you. Perfectly what you asked for.Swyx [00:10:24]: We're recording this ahead of your launch. Uh, we haven't released, we haven't figured out the, the, the name of the launch yet, but what is the product that you're launching? I guess now that we're coinciding this podcast with. Yeah.Will [00:10:36]: So we've basically developed the next version of Exa, which is the ability to get a near perfect list of results of whatever you want. And what that means is you can make a complex query now to Exa, for example, startups working on hardware in SF, and then just get a huge list of all the things that match. And, you know, our goal is if there are 325 startups that match that we find you all of them. And this is just like, there's just like a new experience that's never existed before. It's really like, I don't know how you would go about that right now with current tools and you can apply this same type of like technology to anything. Like, let's say you want, uh, you want to find all the blog posts that talk about Alessio's podcast, um, that have come out in the past year. That is 30 million results. Yeah. Right.Will [00:11:24]: But that, I mean, that would, I'm sure that would be extremely useful to you guys. And like, I don't really know how you would get that full comprehensive list.Swyx [00:11:29]: I just like, how do you, well, there's so many questions with regards to how do you know it's complete, right? Cause you're saying there's only 30 million, 325, whatever. And then how do you do the semantic understanding that it might take, right? So working in hardware, like I might not use the words hardware. I might use the words robotics. I might use the words wearables. I might use like whatever. Yes. So yeah, just tell us more. Yeah. Yeah. Sure. Sure.Will [00:11:53]: So one aspect of this, it's a little subjective. So like certainly providing, you know, at some point we'll provide parameters to the user to like, you know, some sort of threshold to like, uh, gauge like, okay, like this is a cutoff. Like, this is actually not what I mean, because sometimes it's subjective and there needs to be a feedback loop. Like, oh, like it might give you like a few examples and you say, yeah, exactly. And so like, you're, you're kind of like creating a classifier on the fly, but like, that's ultimately how you solve the problem. So the subject, there's a subjectivity problem and then there's a comprehensiveness problem. Those are two different problems. So. Yeah. So you have the comprehensiveness problem. What you basically have to do is you have to put more compute into the query, into the search until you get the full comprehensiveness. Yeah. And I think there's an interesting point here, which is that not all queries are made equal. Some queries just like this blog post one might require scanning, like scavenging, like throughout the whole web in a way that just, just simply requires more compute. You know, at some point there's some amount of compute where you will just be comprehensive. You could imagine, for example, running GPT-4 over the internet. You could imagine running GPT-4 over the entire web and saying like, is this a blog post about Alessio's podcast, like, is this a blog post about Alessio's podcast? And then that would work, right? It would take, you know, a year, maybe cost like a million dollars, but, or many more, but, um, it would work. Uh, the point is that like, given sufficient compute, you can solve the query. And so it's really a question of like, how comprehensive do you want it given your compute budget? I think it's very similar to O1, by the way. And one way of thinking about what we built is like O1 for search, uh, because O1 is all about like, you know, some, some, some questions require more compute than others, and we'll put as much compute into the question as we need to solve it. So similarly with our search, we will put as much compute into the query in order to get comprehensiveness. Yeah.Swyx [00:13:33]: Does that mean you have like some kind of compute budget that I can specify? Yes. Yes. Okay. And like, what are the upper and lower bounds?Will [00:13:42]: Yeah, there's something we're still figuring out. I think like, like everyone is a new paradigm of like variable compute products. Yeah. How do you specify the amount of compute? Like what happens when you. Run out? Do you just like, ah, do you, can you like keep going with it? Like, do you just put in more credits to get more, um, for some, like this can get complex at like the really large compute queries. And like, one thing we do is we give you a preview of what you're going to get, and then you could then spin up like a much larger job, uh, to get like way more results. But yes, there is some compute limit, um, at, at least right now. Yeah. People think of searches as like, oh, it takes 500 milliseconds because we've been conditioned, uh, to have search that takes 500 milliseconds. But like search engines like Google, right. No matter how complex your query to Google, it will take like, you know, roughly 400 milliseconds. But what if searches can take like a minute or 10 minutes or a whole day, what can you then do? And you can do very powerful things. Um, you know, you can imagine, you know, writing a search, going and get a cup of coffee, coming back and you have a perfect list. Like that's okay for a lot of use cases. Yeah.Alessio [00:14:43]: Yeah. I mean, the use case closest to me is venture capital, right? So, uh, no, I mean, eight years ago, I built one of the first like data driven sourcing platforms. So we were. You look at GitHub, Twitter, Product Hunt, all these things, look at interesting things, evaluate them. If you think about some jobs that people have, it's like literally just make a list. If you're like an analyst at a venture firm, your job is to make a list of interesting companies. And then you reach out to them. How do you think about being infrastructure versus like a product you could say, Hey, this is like a product to find companies. This is a product to find things versus like offering more as a blank canvas that people can build on top of. Oh, right. Right.Will [00:15:20]: Uh, we are. We are a search infrastructure company. So we want people to build, uh, on top of us, uh, build amazing products on top of us. But with this one, we try to build something that makes it really easy for users to just log in, put a few, you know, put some credits in and just get like amazing results right away and not have to wait to build some API integration. So we're kind of doing both. Uh, we, we want, we want people to integrate this into all their applications at the same time. We want to just make it really easy to use very similar again to open AI. Like they'll have, they have an API, but they also have. Like a ChatGPT interface so that you could, it's really easy to use, but you could also build it in your applications. Yeah.Alessio [00:15:56]: I'm still trying to wrap my head around a lot of the implications. So, so many businesses run on like information arbitrage, you know, like I know this thing that you don't, especially in investment and financial services. So yeah, now all of a sudden you have these tools for like, oh, actually everybody can get the same information at the same time, the same quality level as an API call. You know, it just kind of changes a lot of things. Yeah.Will [00:16:19]: I think, I think what we're grappling with here. What, what you're just thinking about is like, what is the world like if knowledge is kind of solved, if like any knowledge request you want is just like right there on your computer, it's kind of different from when intelligence is solved. There's like a good, I've written before about like a different super intelligence, super knowledge. Yeah. Like I think that the, the distinction between intelligence and knowledge is actually a pretty good one. They're definitely connected and related in all sorts of ways, but there is a distinction. You could have a world and we are going to have this world where you have like GP five level systems and beyond that could like answer any complex request. Um, unless it requires some. Like, if you say like, uh, you know, give me a list of all the PhDs in New York city who, I don't know, have thought about search before. And even though this, this super intelligence is going to be like, I can't find it on Google, right. Which is kind of crazy. Like we're literally going to have like super intelligences that are using Google. And so if Google can't find them information, there's nothing they could do. They can't find it. So, but if you also have a super knowledge system where it's like, you know, I'm calling this term super knowledge where you just get whatever knowledge you want, then you can pair with a super intelligence system. And then the super intelligence can, we'll never. Be blocked by lack of knowledge.Alessio [00:17:23]: Yeah. You told me this, uh, when we had lunch, I forget how it came out, but we were talking about AGI and whatnot. And you were like, even AGI is going to need search. Yeah.Swyx [00:17:32]: Yeah. Right. Yeah. Um, so we're actually referencing a blog post that you wrote super intelligence and super knowledge. Uh, so I would refer people to that. And this is actually a discussion we've had on the podcast a couple of times. Um, there's so much of model weights that are just memorizing facts. Some of the, some of those might be outdated. Some of them are incomplete or not. Yeah. So like you just need search. So I do wonder, like, is there a maximum language model size that will be the intelligence layer and then the rest is just search, right? Like maybe we should just always use search. And then that sort of workhorse model is just like, and it like, like, like one B or three B parameter model that just drives everything. Yes.Will [00:18:13]: I believe this is a much more optimal system to have a smaller LM. That's really just like an intelligence module. And it makes a call to a search. Tool that's way more efficient because if, okay, I mean the, the opposite of that would be like the LM is so big that can memorize the whole web. That would be like way, but you know, it's not practical at all. I don't, it's not possible to train that at least right now. And Carpathy has actually written about this, how like he could, he could see models moving more and more towards like intelligence modules using various tools. Yeah.Swyx [00:18:39]: So for listeners, that's the, that was him on the no priors podcast. And for us, we talked about this and the, on the Shin Yu and Harrison chase podcasts. I'm doing search in my head. I told you 30 million results. I forgot about our neural link integration. Self-hosted exit.Will [00:18:54]: Yeah. Yeah. No, I do see that that is a much more, much more efficient world. Yeah. I mean, you could also have GB four level systems calling search, but it's just because of the cost of inference. It's just better to have a very efficient search tool and a very efficient LM and they're built for different things. Yeah.Swyx [00:19:09]: I'm just kind of curious. Like it is still something so audacious that I don't want to elide, which is you're, you're, you're building a search engine. Where do you start? How do you, like, are there any reference papers or implementation? That would really influence your thinking, anything like that? Because I don't even know where to start apart from just crawl a bunch of s**t, but there's gotta be more insight than that.Will [00:19:28]: I mean, yeah, there's more insight, but I'm always surprised by like, if you have a group of people who are really focused on solving a problem, um, with the tools today, like there's some in, in software, like there are all sorts of creative solutions that just haven't been thought of before, particularly in the information retrieval field. Yeah. I think a lot of the techniques are just very old, frankly. Like I know how Google and Bing work and. They're just not using new methods. There are all sorts of reasons for that. Like one, like Google has to be comprehensive over the web. So they're, and they have to return in 400 milliseconds. And those two things combined means they are kind of limit and it can't cost too much. They're kind of limited in, uh, what kinds of algorithms they could even deploy at scale. So they end up using like a limited keyword based algorithm. Also like Google was built in a time where like in, you know, in 1998, where we didn't have LMS, we didn't have embeddings. And so they never thought to build those things. And so now they have this like gigantic system that is built on old technology. Yeah. And so a lot of the information retrieval field we found just like thinks in terms of that framework. Yeah. Whereas we came in as like newcomers just thinking like, okay, there here's GB three. It's magical. Obviously we're going to build search that is using that technology. And we never even thought about using keywords really ever. Uh, like we were neural all the way we're building an end to end neural search engine. And just that whole framing just makes us ask different questions, like pursue different lines of work. And there's just a lot of low hanging fruit because no one else is thinking about it. We're just on the frontier of neural search. We just are, um, for, for at web scale, um, because there's just not a lot of people thinking that way about it.Swyx [00:20:57]: Yeah. Maybe let's spell this out since, uh, we're already on this topic, elephants in the room are Perplexity and SearchGPT. That's the, I think that it's all, it's no longer called SearchGPT. I think they call it ChatGPT Search. How would you contrast your approaches to them based on what we know of how they work and yeah, just any, anything in that, in that area? Yeah.Will [00:21:15]: So these systems, there are a few of them now, uh, they basically rely on like traditional search engines like Google or Bing, and then they combine them with like LLMs at the end to, you know, output some power graphics, uh, answering your question. So they like search GPT perplexity. I think they have their own crawlers. No. So there's this important distinction between like having your own search system and like having your own cache of the web. Like for example, so you could create, you could crawl a bunch of the web. Imagine you crawl a hundred billion URLs, and then you create a key value store of like mapping from URL to the document that is technically called an index, but it's not a search algorithm. So then to actually like, when you make a query to search GPT, for example, what is it actually doing it? Let's say it's, it's, it could, it's using the Bing API, uh, getting a list of results and then it could go, it has this cache of like all the contents of those results and then could like bring in the cache, like the index cache, but it's not actually like, it's not like they've built a search engine from scratch over, you know, hundreds of billions of pages. It's like, does that distinction clear? It's like, yeah, you could have like a mapping from URL to documents, but then rely on traditional search engines to actually get the list of results because it's a very hard problem to take. It's not hard. It's not hard to use DynamoDB and, and, and map URLs to documents. It's a very hard problem to take a hundred billion or more documents and given a query, like instantly get the list of results that match. That's a much harder problem that very few entities on, in, on the planet have done. Like there's Google, there's Bing, uh, you know, there's Yandex, but you know, there are not that many companies that are, that are crazy enough to actually build their search engine from scratch when you could just use traditional search APIs.Alessio [00:22:43]: So Google had PageRank as like the big thing. Is there a LLM equivalent or like any. Stuff that you're working on that you want to highlight?Will [00:22:51]: The link prediction objective can be seen as like a neural PageRank because what you're doing is you're predicting the links people share. And so if everyone is sharing some Paul Graham essay about fundraising, then like our model is more likely to predict it. So like inherent in our training objective is this, uh, a sense of like high canonicity and like high quality, but it's more powerful than PageRank. It's strictly more powerful because people might refer to that Paul Graham fundraising essay in like a thousand different ways. And so our model learns all the different ways. That someone refers that Paul Graham, I say, while also learning how important that Paul Graham essay is. Um, so it's like, it's like PageRank on steroids kind of thing. Yeah.Alessio [00:23:26]: I think to me, that's the most interesting thing about search today, like with Google and whatnot, it's like, it's mostly like domain authority. So like if you get back playing, like if you search any AI term, you get this like SEO slop websites with like a bunch of things in them. So this is interesting, but then how do you think about more timeless maybe content? So if you think about, yeah. You know, maybe the founder mode essay, right. It gets shared by like a lot of people, but then you might have a lot of other essays that are also good, but they just don't really get a lot of traction. Even though maybe the people that share them are high quality. How do you kind of solve that thing when you don't have the people authority, so to speak of who's sharing, whether or not they're worth kind of like bumping up? Yeah.Will [00:24:10]: I mean, you do have a lot of control over the training data, so you could like make sure that the training data contains like high quality sources so that, okay. Like if you, if you're. Training data, I mean, it's very similar to like language, language model training. Like if you train on like a bunch of crap, your prediction will be crap. Our model will match the training distribution is trained on. And so we could like, there are lots of ways to tweak the training data to refer to high quality content that we want. Yeah. I would say also this, like this slop that is returned by, by traditional search engines, like Google and Bing, you have the slop is then, uh, transferred into the, these LLMs in like a search GBT or, you know, our other systems like that. Like if slop comes in, slop will go out. And so, yeah, that's another answer to how we're different is like, we're not like traditional search engines. We want to give like the highest quality results and like have full control over whatever you want. If you don't want slop, you get that. And then if you put an LM on top of that, which our customers do, then you just get higher quality results or high quality output.Alessio [00:25:06]: And I use Excel search very often and it's very good. Especially.Swyx [00:25:09]: Wave uses it too.Alessio [00:25:10]: Yeah. Yeah. Yeah. Yeah. Yeah. Like the slop is everywhere, especially when it comes to AI, when it comes to investment. When it comes to all of these things for like, it's valuable to be at the top. And this problem is only going to get worse because. Yeah, no, it's totally. What else is in the toolkit? So you have search API, you have ExaSearch, kind of like the web version. Now you have the list builder. I think you also have web scraping. Maybe just touch on that. Like, I guess maybe people, they want to search and then they want to scrape. Right. So is that kind of the use case that people have? Yeah.Will [00:25:41]: A lot of our customers, they don't just want, because they're building AI applications on top of Exa, they don't just want a list of URLs. They actually want. Like the full content, like cleans, parsed. Markdown. Markdown, maybe chunked, whatever they want, we'll give it to them. And so that's been like huge for customers. Just like getting the URLs and instantly getting the content for each URL is like, and you can do this for 10 or 100 or 1,000 URLs, wherever you want. That's very powerful.Swyx [00:26:05]: Yeah. I think this is the first thing I asked you for when I tried using Exa.Will [00:26:09]: Funny story is like when I built the first version of Exa, it's like, we just happened to store the content. Yes. Like the first 1,024 tokens. Because I just kind of like kept it because I thought of, you know, I don't know why. Really for debugging purposes. And so then when people started asking for content, it was actually pretty easy to serve it. But then, and then we did that, like Exa took off. So the computer's content was so useful. So that was kind of cool.Swyx [00:26:30]: It is. I would say there are other players like Gina, I think is in this space. Firecrawl is in this space. There's a bunch of scraper companies. And obviously scraper is just one part of your stack, but you might as well offer it since you already do it.Will [00:26:43]: Yeah, it makes sense. It's just easy to have an all-in-one solution. And like. We are, you know, building the best scraper in the world. So scraping is a hard problem and it's easy to get like, you know, a good scraper. It's very hard to get a great scraper and it's super hard to get a perfect scraper. So like, and, and scraping really matters to people. Do you have a perfect scraper? Not yet. Okay.Swyx [00:27:05]: The web is increasingly closing to the bots and the scrapers, Twitter, Reddit, Quora, Stack Overflow. I don't know what else. How are you dealing with that? How are you navigating those things? Like, you know. You know, opening your eyes, like just paying them money.Will [00:27:19]: Yeah, no, I mean, I think it definitely makes it harder for search engines. One response is just that there's so much value in the long tail of sites that are open. Okay. Um, and just like, even just searching over those well gets you most of the value. But I mean, there, there is definitely a lot of content that is increasingly not unavailable. And so you could get through that through data partnerships. The bigger we get as a company, the more, the easier it is to just like, uh, make partnerships. But I, I mean, I do see the world as like the future where the. The data, the, the data producers, the content creators will make partnerships with the entities that find that data.Alessio [00:27:53]: Any other fun use case that maybe people are not thinking about? Yeah.Will [00:27:58]: Oh, I mean, uh, there are so many customers. Yeah. What are people doing on AXA? Well, I think dating is a really interesting, uh, application of search that is completely underserved because there's a lot of profiles on the web and a lot of people who want to find love and that I'll use it. They give me. Like, you know, age boundaries, you know, education level location. Yeah. I mean, you want to, what, what do you want to do with data? You want to find like a partner who matches this education level, who like, you know, maybe has written about these types of topics before. Like if you could get a list of all the people like that, like, I think you will unblock a lot of people. I mean, there, I mean, I think this is a very Silicon Valley view of dating for sure. And I'm, I'm well aware of that, but it's just an interesting application of like, you know, I would love to meet like an intellectual partner, um, who like shares a lot of ideas. Yeah. Like if you could do that through better search and yeah.Swyx [00:28:48]: But what is it with Jeff? Jeff has already set me up with a few people. So like Jeff, I think it's my personal exit.Will [00:28:55]: my mom's actually a matchmaker and has got a lot of married. Yeah. No kidding. Yeah. Yeah. Search is built into the book. It's in your jeans. Yeah. Yeah.Swyx [00:29:02]: Yeah. Other than dating, like I know you're having quite some success in colleges. I would just love to map out some more use cases so that our listeners can just use those examples to think about use cases for XR, right? Because it's such a general technology that it's hard to. Uh, really pin down, like, what should I use it for and what kind of products can I build with it?Will [00:29:20]: Yeah, sure. So, I mean, there are so many applications of XR and we have, you know, many, many companies using us for very diverse range of use cases, but I'll just highlight some interesting ones. Like one customer, a big customer is using us to, um, basically build like a, a writing assistant for students who want to write, uh, research papers. And basically like XR will search for, uh, like a list of research papers related to what the student is writing. And then this product has. Has like an LLM that like summarizes the papers to basically it's like a next word prediction, but in, uh, you know, prompted by like, you know, 20 research papers that X has returned. It's like literally just doing their homework for them. Yeah. Yeah. the key point is like, it's, it's, uh, you know, it's, it's, you know, research is, is a really hard thing to do and you need like high quality content as input.Swyx [00:30:08]: Oh, so we've had illicit on the podcast. I think it's pretty similar. Uh, they, they do focus pretty much on just, just research papers and, and that research. Basically, I think dating, uh, research, like I just wanted to like spell out more things, like just the big verticals.Will [00:30:23]: Yeah, yeah, no, I mean, there, there are so many use cases. So finance we talked about, yeah. I mean, one big vertical is just finding a list of companies, uh, so it's useful for VCs, like you said, who want to find like a list of competitors to a specific company they're investigating or just a list of companies in some field. Like, uh, there was one VC that told me that him and his team, like we're using XR for like eight hours straight. Like, like that. For many days on end, just like, like, uh, doing like lots of different queries of different types, like, oh, like all the companies in AI for law or, uh, all the companies for AI for, uh, construction and just like getting lists of things because you just can't find this information with, with traditional search engines. And then, you know, finding companies is also useful for, for selling. If you want to find, you know, like if we want to find a list of, uh, writing assistants to sell to, then we can just, we just use XR ourselves to find that is actually how we found a lot of our customers. Ooh, you can find your own customers using XR. Oh my God. I, in the spirit of. Uh, using XR to bolster XR, like recruiting is really helpful. It is really great use case of XR, um, because we can just get like a list of, you know, people who thought about search and just get like a long list and then, you know, reach out to those people.Swyx [00:31:29]: When you say thought about, are you, are you thinking LinkedIn, Twitter, or are you thinking just blogs?Will [00:31:33]: Or they've written, I mean, it's pretty general. So in that case, like ideally XR would return like the, the really blogs written by people who have just. So if I don't blog, I don't show up to XR, right? Like I have to blog. well, I mean, you could show up. That's like an incentive for people to blog.Swyx [00:31:47]: Well, if you've written about, uh, search in on Twitter and we, we do, we do index a bunch of tweets and then we, we should be able to service that. Yeah. Um, I mean, this is something I tell people, like you have to make yourself discoverable to the web, uh, you know, it's called learning in public, but like, it's even more imperative now because otherwise you don't exist at all.Will [00:32:07]: Yeah, no, no, this is a huge, uh, thing, which is like search engines completely influence. They have downstream effects. They influence the internet itself. They influence what people. Choose to create. And so Google, because they're a keyword based search engine, people like kind of like keyword stuff. Yeah. They're, they're, they're incentivized to create things that just match a lot of keywords, which is not very high quality. Uh, whereas XR is a search algorithm that, uh, optimizes for like high quality and actually like matching what you mean. And so people are incentivized to create content that is high quality, that like the create content that they know will be found by the right person. So like, you know, if I am a search researcher and I want to be found. By XR, I should blog about search and all the things I'm building because, because now we have a search engine like XR that's powerful enough to find them. And so the search engine will influence like the downstream internet in all sorts of amazing ways. Yeah. Uh, whatever the search engine optimizes for is what the internet looks like. Yeah.Swyx [00:33:01]: Are you familiar with the term? McLuhanism? No, it's not. Uh, it's this concept that, uh, like first we shape tools and then the tools shape us. Okay. Yeah. Uh, so there's like this reflexive connection between the things we search for and the things that get searched. Yes. So like once you change the tool. The tool that searches the, the, the things that get searched also change. Yes.Will [00:33:18]: I mean, there was a clear example of that with 30 years of Google. Yeah, exactly. Google has basically trained us to think of search and Google has Google is search like in people's heads. Right. It's one, uh, hard part about XR is like, uh, ripping people away from that notion of search and expanding their sense of what search could be. Because like when people think search, they think like a few keywords, or at least they used to, they think of a few keywords and that's it. They don't think to make these like really complex paragraph long requests for information and get a perfect list. ChatGPT was an interesting like thing that expanded people's understanding of search because you start using ChatGPT for a few hours and you go back to Google and you like paste in your code and Google just doesn't work and you're like, oh, wait, it, Google doesn't do work that way. So like ChatGPT expanded our understanding of what search can be. And I think XR is, uh, is part of that. We want to expand people's notion, like, Hey, you could actually get whatever you want. Yeah.Alessio [00:34:06]: I search on XR right now, people writing about learning in public. I was like, is it gonna come out with Alessio? Am I, am I there? You're not because. Bro. It's. So, no, it's, it's so about, because it thinks about learning, like in public, like public schools and like focuses more on that. You know, it's like how, when there are like these highly overlapping things, like this is like a good result based on the query, you know, but like, how do I get to Alessio? Right. So if you're like in these subcultures, I don't think this would work in Google well either, you know, but I, I don't know if you have any learnings.Swyx [00:34:40]: No, I'm the first result on Google.Alessio [00:34:42]: People writing about learning. In public, you're not first result anymore, I guess.Swyx [00:34:48]: Just type learning public in Google.Alessio [00:34:49]: Well, yeah, yeah, yeah, yeah. But this is also like, this is in Google, it doesn't work either. That's what I'm saying. It's like how, when you have like a movement.Will [00:34:56]: There's confusion about the, like what you mean, like your intention is a little, uh. Yeah.Alessio [00:35:00]: It's like, yeah, I'm using, I'm using a term that like I didn't invent, but I'm kind of taking over, but like, they're just so much about that term already that it's hard to overcome. If that makes sense, because public schools is like, well, it's, it's hard to overcome.Will [00:35:14]: Public schools, you know, so there's the right solution to this, which is to specify more clearly what you mean. And I'm not expecting you to do that, but so the, the right interface to search is actually an LLM.Swyx [00:35:25]: Like you should be talking to an LLM about what you want and the LLM translates its knowledge of you or knowledge of what people usually mean into a query that excellent uses, which you have called auto prompts, right?Will [00:35:35]: Or, yeah, but it's like a very light version of that. And really it's just basically the right answer is it's the wrong interface and like very soon interface to search and really to everything will be LLM. And the LLM just has a full knowledge of you, right? So we're kind of building for that world. We're skating to where the puck is going to be. And so since we're moving to a world where like LLMs are interfaced to everything, you should build a search engine that can handle complex LLM queries, queries that come from LLMs. Because you're probably too lazy, I'm too lazy too, to write like a whole paragraph explaining, okay, this is what I mean by this word. But an LLM is not lazy. And so like the LLM will spit out like a paragraph or more explaining exactly what it wants. You need a search engine that can handle that. Traditional search engines like Google or Bing, they're actually... Designed for humans typing keywords. If you give a paragraph to Google or Bing, they just completely fail. And so Exa can handle paragraphs and we want to be able to handle it more and more until it's like perfect.Alessio [00:36:24]: What about opinions? Do you have lists? When you think about the list product, do you think about just finding entries? Do you think about ranking entries? I'll give you a dumb example. So on Lindy, I've been building the spot that every week gives me like the top fantasy football waiver pickups. But every website is like different opinions. I'm like, you should pick up. These five players, these five players. When you're making lists, do you want to be kind of like also ranking and like telling people what's best? Or like, are you mostly focused on just surfacing information?Will [00:36:56]: There's a really good distinction between filtering to like things that match your query and then ranking based on like what is like your preferences. And ranking is like filtering is objective. It's like, does this document match what you asked for? Whereas ranking is more subjective. It's like, what is the best? Well, it depends what you mean by best, right? So first, first table stakes is let's get the filtering into a perfect place where you actually like every document matches what you asked for. No surgeon can do that today. And then ranking, you know, there are all sorts of interesting ways to do that where like you've maybe for, you know, have the user like specify more clearly what they mean by best. You could do it. And if the user doesn't specify, you do your best, you do your best based on what people typically mean by best. But ideally, like the user can specify, oh, when I mean best, I actually mean ranked by the, you know, the number of people who visited that site. Let's say is, is one example ranking or, oh, what I mean by best, let's say you're listing companies. What I mean by best is like the ones that have, uh, you know, have the most employees or something like that. Like there are all sorts of ways to rank a list of results that are not captured by something as subjective as best. Yeah. Yeah.Alessio [00:38:00]: I mean, it's like, who are the best NBA players in the history? It's like everybody has their own. Right.Will [00:38:06]: Right. But I mean, the, the, the search engine should definitely like, even if you don't specify it, it should do as good of a job as possible. Yeah. Yeah. No, no, totally. Yeah. Yeah. Yeah. Yeah. It's a new topic to people because we're not used to a search engine that can handle like a very complex ranking system. Like you think to type in best basketball players and not something more specific because you know, that's the only thing Google could handle. But if Google could handle like, oh, basketball players ranked by like number of shots scored on average per game, then you would do that. But you know, they can't do that. So.Swyx [00:38:32]: Yeah. That's fascinating. So you haven't used the word agents, but you're kind of building a search agent. Do you believe that that is agentic in feature? Do you think that term is distracting?Will [00:38:42]: I think it's a good term. I do think everything will eventually become agentic. And so then the term will lose power, but yes, like what we're building is agentic it in a sense that it takes actions. It decides when to go deeper into something, it has a loop, right? It feels different from traditional search, which is like an algorithm, not an agent. Ours is a combination of an algorithm and an agent.Swyx [00:39:05]: I think my reflection from seeing this in the coding space where there's basically sort of classic. Framework for thinking about this stuff is the self-driving levels of autonomy, right? Level one to five, typically the level five ones all failed because there's full autonomy and we're not, we're not there yet. And people like control. People like to be in the loop. So the, the, the level ones was co-pilot first and now it's like cursor and whatever. So I feel like if it's too agentic, it's too magical, like, like a, like a one shot, I stick a, stick a paragraph into the text box and then it spits it back to me. It might feel like I'm too disconnected from the process and I don't trust it. As opposed to something where I'm more intimately involved with the research product. I see. So like, uh, wait, so the earlier versions are, so if trying to stick to the example of the basketball thing, like best basketball player, but instead of best, you, you actually get to customize it with like, whatever the metric is that you, you guys care about. Yeah. I'm still not a basketballer, but, uh, but, but, you know, like, like B people like to be in my, my thesis is that agents level five agents failed because people like to. To kind of have drive assist rather than full self-driving.Will [00:40:15]: I mean, a lot of this has to do with how good agents are. Like at some point, if agents for coding are better than humans at all tests and then humans block, yeah, we're not there yet.Swyx [00:40:25]: So like in a world where we're not there yet, what you're pitching us is like, you're, you're kind of saying you're going all the way there. Like I kind of, I think all one is also very full, full self-driving. You don't get to see the plan. You don't get to affect the plan yet. You just fire off a query and then it goes away for a couple of minutes and comes back. Right. Which is effectively what you're saying you're going to do too. And you think there's.Will [00:40:42]: There's a, there's an in-between. I saw. Okay. So in building this product, we're exploring new interfaces because what does it mean to kick off a search that goes and takes 10 minutes? Like, is that a good interface? Because what if the search is actually wrong or it's not exactly, exactly specified to what you mean, which is why you get previews. Yeah. You get previews. So it is iterative, but ultimately once you've specified exactly what you mean, then you kind of do just want to kick off a batch job. Right. So perhaps what you're getting at is like, uh, there's this barrier with agents where you have to like explain the full context of what you mean, and a lot of failure modes happen when you have, when you don't. Yeah. There's failure modes from the agent, just not being smart enough. And then there's failure modes from the agent, not understanding exactly what you mean. And there's a lot of context that is shared between humans that is like lost between like humans and, and this like new creature.Alessio [00:41:32]: Yeah. Yeah. Because people don't know what's going on. I mean, to me, the best example of like system prompts is like, why are you writing? You're a helpful assistant. Like. Of course you should be an awful, but people don't yet know, like, can I assume that, you know, that, you know, it's like, why did the, and now people write, oh, you're a very smart software engineer, but like, you never made, you never make mistakes. Like, were you going to try and make mistakes before? So I think people don't yet have an understanding, like with, with driving people know what good driving is. It's like, don't crash, stay within kind of like a certain speed range. It's like, follow the directions. It's like, I don't really have to explain all of those things. I hope. But with. AI and like models and like search, people are like, okay, what do you actually know? What are like your assumptions about how search, how you're going to do search? And like, can I trust it? You know, can I influence it? So I think that's kind of the, the middle ground, like before you go ahead and like do all the search, it's like, can I see how you're doing it? And then maybe help show your work kind of like, yeah, steer you. Yeah. Yeah.Will [00:42:32]: No, I mean, yeah. Sure. Saying, even if you've crafted a great system prompt, you want to be part of the process itself. Uh, because the system prompt doesn't, it doesn't capture everything. Right. So yeah. A system prompt is like, you get to choose the person you work with. It's like, oh, like I want, I want a software engineer who thinks this way about code. But then even once you've chosen that person, you can't just give them a high level command and they go do it perfectly. You have to be part of that process. So yeah, I agree.Swyx [00:42:58]: Just a side note for my system, my favorite system, prompt programming anecdote now is the Apple intelligence system prompt that someone, someone's a prompt injected it and seen it. And like the Apple. Intelligence has the words, like, please don't, don't hallucinate. And it's like, of course we don't want you to hallucinate. Right. Like, so it's exactly that, that what you're talking about, like we should train this behavior into the model, but somehow we still feel the need to inject into the prompt. And I still don't even think that we are very scientific about it. Like it, I think it's almost like cargo culting. Like we have this like magical, like turn around three times, throw salt over your shoulder before you do something. And like, it worked the last time. So let's just do it the same time now. And like, we do, there's no science to this.Will [00:43:35]: I do think a lot of these problems might be ironed out in future versions. Right. So, and like, they might, they might hide the details from you. So it's like, they actually, all of them have a system prompt. That's like, you are a helpful assistant. You don't actually have to include it, even though it might actually be the way they've implemented in the backend. It should be done in RLE AF.Swyx [00:43:52]: Okay. Uh, one question I was just kind of curious about this episode is I'm going to try to frame this in terms of this, the general AI search wars, you know, you're, you're one player in that, um, there's perplexity, chat, GPT, search, and Google, but there's also like the B2B side, uh, we had. Drew Houston from Dropbox on, and he's competing with Glean, who've, uh, we've also had DD from, from Glean on, is there an appetite for Exa for my company's documents?Will [00:44:19]: There is appetite, but I think we have to be disciplined, focused, disciplined. I mean, we're already taking on like perfect web search, which is a lot. Um, but I mean, ultimately we want to build a perfect search engine, which definitely for a lot of queries involves your, your personal information, your company's information. And so, yeah, I mean, the grandest vision of Exa is perfect search really over everything, every domain, you know, we're going to have an Exa satellite, uh, because, because satellites can gather information that, uh, is not available publicly. Uh, gotcha. Yeah.Alessio [00:44:51]: Can we talk about AGI? We never, we never talk about AGI, but you had, uh, this whole tweet about, oh, one being the biggest kind of like AI step function towards it. Why does it feel so important to you? I know there's kind of like always criticism and saying, Hey, it's not the smartest son is better. It's like, blah, blah, blah. What? You choose C. So you say, this is what Ilias see or Sam see what they will see.Will [00:45:13]: I've just, I've just, you know, been connecting the dots. I mean, this was the key thing that a bunch of labs were working on, which is like, can you create a reward signal? Can you teach yourself based on a reward signal? Whether you're, if you're trying to learn coding or math, if you could have one model say, uh, be a grading system that says like you have successfully solved this programming assessment and then one model, like be the generative system. That's like, here are a bunch of programming assessments. You could train on that. It's basically whenever you could create a reward signal for some task, you could just generate a bunch of tasks for yourself. See that like, oh, on two of these thousand, you did well. And then you just train on that data. It's basically like, I mean, creating your own data for yourself and like, you know, all the labs working on that opening, I built the most impressive product doing that. And it's just very, it's very easy now to see how that could like scale to just solving, like, like solving programming or solving mathematics, which sounds crazy, but everything about our world right now is crazy.Alessio [00:46:07]: Um, and so I think if you remove that whole, like, oh, that's impossible, and you just think really clearly about like, what's now possible with like what, what they've done with O1, it's easy to see how that scales. How do you think about older GPT models then? Should people still work on them? You know, if like, obviously they just had the new Haiku, like, is it even worth spending time, like making these models better versus just, you know, Sam talked about O2 at that day. So obviously they're, they're spending a lot of time in it, but then you have maybe. The GPU poor, which are still working on making Lama good. Uh, and then you have the follower labs that do not have an O1 like model out yet. Yeah.Will [00:46:47]: This kind of gets into like, uh, what will the ecosystem of, of models be like in the future? And is there room is, is everything just gonna be O1 like models? I think, well, I mean, there's definitely a question of like inference speed and if certain things like O1 takes a long time, because that's the thing. Well, I mean, O1 is, is two things. It's like one it's it's use it's bootstrapping itself. It's teaching itself. And so the base model is smarter. But then it also has this like inference time compute where it could like spend like many minutes or many hours thinking. And so even the base model, which is also fast, it doesn't have to take minutes. It could take is, is better, smarter. I believe all models will be trained with this paradigm. Like you'll want to train on the best data, but there will be many different size models from different, very many different like companies, I believe. Yeah. Because like, I don't, yeah, I mean, it's hard, hard to predict, but I don't think opening eye is going to dominate like every possible LLM for every possible. Use case. I think for a lot of things, like you just want the fastest model and that might not involve O1 methods at all.Swyx [00:47:42]: I would say if you were to take the exit being O1 for search, literally, you really need to prioritize search trajectories, like almost maybe paying a bunch of grad students to go research things. And then you kind of track what they search and what the sequence of searching is, because it seems like that is the gold mine here, like the chain of thought or the thinking trajectory. Yeah.Will [00:48:05]: When it comes to search, I've always been skeptical. I've always been skeptical of human labeled data. Okay. Yeah, please. We tried something at our company at Exa recently where me and a bunch of engineers on the team like labeled a bunch of queries and it was really hard. Like, you know, you have all these niche queries and you're looking at a bunch of results and you're trying to identify which is matched to query. It's talking about, you know, the intricacies of like some biological experiment or something. I have no idea. Like, I don't know what matches and what, what labelers like me tend to do is just match by keyword. I'm like, oh, I don't know. Oh, like this document matches a bunch of keywords, so it must be good. But then you're actually completely missing the meaning of the document. Whereas an LLM like GB4 is really good at labeling. And so I actually think like you just we get by, which we are right now doing using like LLM

Tell us what you think about this podcast!Understanding the biblical foundation and structure of church leadership is essential for every pastor. This lesson explores the roles of pastors, elders, and deacons, emphasizing order, accountability, and the Apostolic Pentecostal approach to leading a church according to scriptural principles.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!Understanding the biblical foundation and structure of church leadership is essential for every pastor. This lesson explores the roles of pastors, elders, and deacons, emphasizing order, accountability, and the Apostolic Pentecostal approach to leading a church according to scriptural principles.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!Understanding the biblical foundation and structure of church leadership is essential for every pastor. This lesson explores the roles of pastors, elders, and deacons, emphasizing order, accountability, and the Apostolic Pentecostal approach to leading a church according to scriptural principles.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Applications for the 2025 AI Engineer Summit are up, and you can save the date for AIE Singapore in April and AIE World's Fair 2025 in June.Happy new year, and thanks for 100 great episodes! Please let us know what you want to see/hear for the next 100!Full YouTube Episode with Slides/ChartsLike and subscribe and hit that bell to get notifs!Timestamps* 00:00 Welcome to the 100th Episode!* 00:19 Reflecting on the Journey* 00:47 AI Engineering: The Rise and Impact* 03:15 Latent Space Live and AI Conferences* 09:44 The Competitive AI Landscape* 21:45 Synthetic Data and Future Trends* 35:53 Creative Writing with AI* 36:12 Legal and Ethical Issues in AI* 38:18 The Data War: GPU Poor vs. GPU Rich* 39:12 The Rise of GPU Ultra Rich* 40:47 Emerging Trends in AI Models* 45:31 The Multi-Modality War* 01:05:31 The Future of AI Benchmarks* 01:13:17 Pionote and Frontier Models* 01:13:47 Niche Models and Base Models* 01:14:30 State Space Models and RWKB* 01:15:48 Inference Race and Price Wars* 01:22:16 Major AI Themes of the Year* 01:22:48 AI Rewind: January to March* 01:26:42 AI Rewind: April to June* 01:33:12 AI Rewind: July to September* 01:34:59 AI Rewind: October to December* 01:39:53 Year-End Reflections and PredictionsTranscript[00:00:00] Welcome to the 100th Episode![00:00:00] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host Swyx for the 100th time today.[00:00:12] swyx: Yay, um, and we're so glad that, yeah, you know, everyone has, uh, followed us in this journey. How do you feel about it? 100 episodes.[00:00:19] Alessio: Yeah, I know.[00:00:19] Reflecting on the Journey[00:00:19] Alessio: Almost two years that we've been doing this. We've had four different studios. Uh, we've had a lot of changes. You know, we used to do this lightning round. When we first started that we didn't like, and we tried to change the question. The answer[00:00:32] swyx: was cursor and perplexity.[00:00:34] Alessio: Yeah, I love mid journey. It's like, do you really not like anything else?[00:00:38] Alessio: Like what's, what's the unique thing? And I think, yeah, we, we've also had a lot more research driven content. You know, we had like 3DAO, we had, you know. Jeremy Howard, we had more folks like that.[00:00:47] AI Engineering: The Rise and Impact[00:00:47] Alessio: I think we want to do more of that too in the new year, like having, uh, some of the Gemini folks, both on the research and the applied side.[00:00:54] Alessio: Yeah, but it's been a ton of fun. I think we both started, I wouldn't say as a joke, we were kind of like, Oh, we [00:01:00] should do a podcast. And I think we kind of caught the right wave, obviously. And I think your rise of the AI engineer posts just kind of get people. Sombra to congregate, and then the AI engineer summit.[00:01:11] Alessio: And that's why when I look at our growth chart, it's kind of like a proxy for like the AI engineering industry as a whole, which is almost like, like, even if we don't do that much, we keep growing just because there's so many more AI engineers. So did you expect that growth or did you expect that would take longer for like the AI engineer thing to kind of like become, you know, everybody talks about it today.[00:01:32] swyx: So, the sign of that, that we have won is that Gartner puts it at the top of the hype curve right now. So Gartner has called the peak in AI engineering. I did not expect, um, to what level. I knew that I was correct when I called it because I did like two months of work going into that. But I didn't know, You know, how quickly it could happen, and obviously there's a chance that I could be wrong.[00:01:52] swyx: But I think, like, most people have come around to that concept. Hacker News hates it, which is a good sign. But there's enough people that have defined it, you know, GitHub, when [00:02:00] they launched GitHub Models, which is the Hugging Face clone, they put AI engineers in the banner, like, above the fold, like, in big So I think it's like kind of arrived as a meaningful and useful definition.[00:02:12] swyx: I think people are trying to figure out where the boundaries are. I think that was a lot of the quote unquote drama that happens behind the scenes at the World's Fair in June. Because I think there's a lot of doubt or questions about where ML engineering stops and AI engineering starts. That's a useful debate to be had.[00:02:29] swyx: In some sense, I actually anticipated that as well. So I intentionally did not. Put a firm definition there because most of the successful definitions are necessarily underspecified and it's actually useful to have different perspectives and you don't have to specify everything from the outset.[00:02:45] Alessio: Yeah, I was at um, AWS reInvent and the line to get into like the AI engineering talk, so to speak, which is, you know, applied AI and whatnot was like, there are like hundreds of people just in line to go in.[00:02:56] Alessio: I think that's kind of what enabled me. People, right? Which is what [00:03:00] you kind of talked about. It's like, Hey, look, you don't actually need a PhD, just, yeah, just use the model. And then maybe we'll talk about some of the blind spots that you get as an engineer with the earlier posts that we also had on on the sub stack.[00:03:11] Alessio: But yeah, it's been a heck of a heck of a two years.[00:03:14] swyx: Yeah.[00:03:15] Latent Space Live and AI Conferences[00:03:15] swyx: You know, I was, I was trying to view the conference as like, so NeurIPS is I think like 16, 17, 000 people. And the Latent Space Live event that we held there was 950 signups. I think. The AI world, the ML world is still very much research heavy. And that's as it should be because ML is very much in a research phase.[00:03:34] swyx: But as we move this entire field into production, I think that ratio inverts into becoming more engineering heavy. So at least I think engineering should be on the same level, even if it's never as prestigious, like it'll always be low status because at the end of the day, you're manipulating APIs or whatever.[00:03:51] swyx: But Yeah, wrapping GPTs, but there's going to be an increasing stack and an art to doing these, these things well. And I, you know, I [00:04:00] think that's what we're focusing on for the podcast, the conference and basically everything I do seems to make sense. And I think we'll, we'll talk about the trends here that apply.[00:04:09] swyx: It's, it's just very strange. So, like, there's a mix of, like, keeping on top of research while not being a researcher and then putting that research into production. So, like, people always ask me, like, why are you covering Neuralibs? Like, this is a ML research conference and I'm like, well, yeah, I mean, we're not going to, to like, understand everything Or reproduce every single paper, but the stuff that is being found here is going to make it through into production at some point, you hope.[00:04:32] swyx: And then actually like when I talk to the researchers, they actually get very excited because they're like, oh, you guys are actually caring about how this goes into production and that's what they really really want. The measure of success is previously just peer review, right? Getting 7s and 8s on their um, Academic review conferences and stuff like citations is one metric, but money is a better metric.[00:04:51] Alessio: Money is a better metric. Yeah, and there were about 2200 people on the live stream or something like that. Yeah, yeah. Hundred on the live stream. So [00:05:00] I try my best to moderate, but it was a lot spicier in person with Jonathan and, and Dylan. Yeah, that it was in the chat on YouTube.[00:05:06] swyx: I would say that I actually also created.[00:05:09] swyx: Layen Space Live in order to address flaws that are perceived in academic conferences. This is not NeurIPS specific, it's ICML, NeurIPS. Basically, it's very sort of oriented towards the PhD student, uh, market, job market, right? Like literally all, basically everyone's there to advertise their research and skills and get jobs.[00:05:28] swyx: And then obviously all the, the companies go there to hire them. And I think that's great for the individual researchers, but for people going there to get info is not great because you have to read between the lines, bring a ton of context in order to understand every single paper. So what is missing is effectively what I ended up doing, which is domain by domain, go through and recap the best of the year.[00:05:48] swyx: Survey the field. And there are, like NeurIPS had a, uh, I think ICML had a like a position paper track, NeurIPS added a benchmarks, uh, datasets track. These are ways in which to address that [00:06:00] issue. Uh, there's always workshops as well. Every, every conference has, you know, a last day of workshops and stuff that provide more of an overview.[00:06:06] swyx: But they're not specifically prompted to do so. And I think really, uh, Organizing a conference is just about getting good speakers and giving them the correct prompts. And then they will just go and do that thing and they do a very good job of it. So I think Sarah did a fantastic job with the startups prompt.[00:06:21] swyx: I can't list everybody, but we did best of 2024 in startups, vision, open models. Post transformers, synthetic data, small models, and agents. And then the last one was the, uh, and then we also did a quick one on reasoning with Nathan Lambert. And then the last one, obviously, was the debate that people were very hyped about.[00:06:39] swyx: It was very awkward. And I'm really, really thankful for John Franco, basically, who stepped up to challenge Dylan. Because Dylan was like, yeah, I'll do it. But He was pro scaling. And I think everyone who is like in AI is pro scaling, right? So you need somebody who's ready to publicly say, no, we've hit a wall.[00:06:57] swyx: So that means you're saying Sam Altman's wrong. [00:07:00] You're saying, um, you know, everyone else is wrong. It helps that this was the day before Ilya went on, went up on stage and then said pre training has hit a wall. And data has hit a wall. So actually Jonathan ended up winning, and then Ilya supported that statement, and then Noam Brown on the last day further supported that statement as well.[00:07:17] swyx: So it's kind of interesting that I think the consensus kind of going in was that we're not done scaling, like you should believe in a better lesson. And then, four straight days in a row, you had Sepp Hochreiter, who is the creator of the LSTM, along with everyone's favorite OG in AI, which is Juergen Schmidhuber.[00:07:34] swyx: He said that, um, we're pre trading inside a wall, or like, we've run into a different kind of wall. And then we have, you know John Frankel, Ilya, and then Noam Brown are all saying variations of the same thing, that we have hit some kind of wall in the status quo of what pre trained, scaling large pre trained models has looked like, and we need a new thing.[00:07:54] swyx: And obviously the new thing for people is some make, either people are calling it inference time compute or test time [00:08:00] compute. I think the collective terminology has been inference time, and I think that makes sense because test time, calling it test, meaning, has a very pre trained bias, meaning that the only reason for running inference at all is to test your model.[00:08:11] swyx: That is not true. Right. Yeah. So, so, I quite agree that. OpenAI seems to have adopted, or the community seems to have adopted this terminology of ITC instead of TTC. And that, that makes a lot of sense because like now we care about inference, even right down to compute optimality. Like I actually interviewed this author who recovered or reviewed the Chinchilla paper.[00:08:31] swyx: Chinchilla paper is compute optimal training, but what is not stated in there is it's pre trained compute optimal training. And once you start caring about inference, compute optimal training, you have a different scaling law. And in a way that we did not know last year.[00:08:45] Alessio: I wonder, because John is, he's also on the side of attention is all you need.[00:08:49] Alessio: Like he had the bet with Sasha. So I'm curious, like he doesn't believe in scaling, but he thinks the transformer, I wonder if he's still. So, so,[00:08:56] swyx: so he, obviously everything is nuanced and you know, I told him to play a character [00:09:00] for this debate, right? So he actually does. Yeah. He still, he still believes that we can scale more.[00:09:04] swyx: Uh, he just assumed the character to be very game for, for playing this debate. So even more kudos to him that he assumed a position that he didn't believe in and still won the debate.[00:09:16] Alessio: Get rekt, Dylan. Um, do you just want to quickly run through some of these things? Like, uh, Sarah's presentation, just the highlights.[00:09:24] swyx: Yeah, we can't go through everyone's slides, but I pulled out some things as a factor of, like, stuff that we were going to talk about. And we'll[00:09:30] Alessio: publish[00:09:31] swyx: the rest. Yeah, we'll publish on this feed the best of 2024 in those domains. And hopefully people can benefit from the work that our speakers have done.[00:09:39] swyx: But I think it's, uh, these are just good slides. And I've been, I've been looking for a sort of end of year recaps from, from people.[00:09:44] The Competitive AI Landscape[00:09:44] swyx: The field has progressed a lot. You know, I think the max ELO in 2023 on LMSys used to be 1200 for LMSys ELOs. And now everyone is at least at, uh, 1275 in their ELOs, and this is across Gemini, Chadjibuti, [00:10:00] Grok, O1.[00:10:01] swyx: ai, which with their E Large model, and Enthopic, of course. It's a very, very competitive race. There are multiple Frontier labs all racing, but there is a clear tier zero Frontier. And then there's like a tier one. It's like, I wish I had everything else. Tier zero is extremely competitive. It's effectively now three horse race between Gemini, uh, Anthropic and OpenAI.[00:10:21] swyx: I would say that people are still holding out a candle for XAI. XAI, I think, for some reason, because their API was very slow to roll out, is not included in these metrics. So it's actually quite hard to put on there. As someone who also does charts, XAI is continually snubbed because they don't work well with the benchmarking people.[00:10:42] swyx: Yeah, yeah, yeah. It's a little trivia for why XAI always gets ignored. The other thing is market share. So these are slides from Sarah. We have it up on the screen. It has gone from very heavily open AI. So we have some numbers and estimates. These are from RAMP. Estimates of open AI market share in [00:11:00] December 2023.[00:11:01] swyx: And this is basically, what is it, GPT being 95 percent of production traffic. And I think if you correlate that with stuff that we asked. Harrison Chase on the LangChain episode, it was true. And then CLAUD 3 launched mid middle of this year. I think CLAUD 3 launched in March, CLAUD 3. 5 Sonnet was in June ish.[00:11:23] swyx: And you can start seeing the market share shift towards opening, uh, towards that topic, uh, very, very aggressively. The more recent one is Gemini. So if I scroll down a little bit, this is an even more recent dataset. So RAM's dataset ends in September 2 2. 2024. Gemini has basically launched a price war at the low end, uh, with Gemini Flash, uh, being basically free for personal use.[00:11:44] swyx: Like, I think people don't understand the free tier. It's something like a billion tokens per day. Unless you're trying to abuse it, you cannot really exhaust your free tier on Gemini. They're really trying to get you to use it. They know they're in like third place, um, fourth place, depending how you, how you count.[00:11:58] swyx: And so they're going after [00:12:00] the Lower tier first, and then, you know, maybe the upper tier later, but yeah, Gemini Flash, according to OpenRouter, is now 50 percent of their OpenRouter requests. Obviously, these are the small requests. These are small, cheap requests that are mathematically going to be more.[00:12:15] swyx: The smart ones obviously are still going to OpenAI. But, you know, it's a very, very big shift in the market. Like basically 2023, 2022, To going into 2024 opening has gone from nine five market share to Yeah. Reasonably somewhere between 50 to 75 market share.[00:12:29] Alessio: Yeah. I'm really curious how ramped does the attribution to the model?[00:12:32] Alessio: If it's API, because I think it's all credit card spin. . Well, but it's all, the credit card doesn't say maybe. Maybe the, maybe when they do expenses, they upload the PDF, but yeah, the, the German I think makes sense. I think that was one of my main 2024 takeaways that like. The best small model companies are the large labs, which is not something I would have thought that the open source kind of like long tail would be like the small model.[00:12:53] swyx: Yeah, different sizes of small models we're talking about here, right? Like so small model here for Gemini is AB, [00:13:00] right? Uh, mini. We don't know what the small model size is, but yeah, it's probably in the double digits or maybe single digits, but probably double digits. The open source community has kind of focused on the one to three B size.[00:13:11] swyx: Mm-hmm . Yeah. Maybe[00:13:12] swyx: zero, maybe 0.5 B uh, that's moon dream and that is small for you then, then that's great. It makes sense that we, we have a range for small now, which is like, may, maybe one to five B. Yeah. I'll even put that at, at, at the high end. And so this includes Gemma from Gemini as well. But also includes the Apple Foundation models, which I think Apple Foundation is 3B.[00:13:32] Alessio: Yeah. No, that's great. I mean, I think in the start small just meant cheap. I think today small is actually a more nuanced discussion, you know, that people weren't really having before.[00:13:43] swyx: Yeah, we can keep going. This is a slide that I smiley disagree with Sarah. She's pointing to the scale SEAL leaderboard. I think the Researchers that I talked with at NeurIPS were kind of positive on this because basically you need private test [00:14:00] sets to prevent contamination.[00:14:02] swyx: And Scale is one of maybe three or four people this year that has really made an effort in doing a credible private test set leaderboard. Llama405B does well compared to Gemini and GPT 40. And I think that's good. I would say that. You know, it's good to have an open model that is that big, that does well on those metrics.[00:14:23] swyx: But anyone putting 405B in production will tell you, if you scroll down a little bit to the artificial analysis numbers, that it is very slow and very expensive to infer. Um, it doesn't even fit on like one node. of, uh, of H100s. Cerebras will be happy to tell you they can serve 4 or 5B on their super large chips.[00:14:42] swyx: But, um, you know, if you need to do anything custom to it, you're still kind of constrained. So, is 4 or 5B really that relevant? Like, I think most people are basically saying that they only use 4 or 5B as a teacher model to distill down to something. Even Meta is doing it. So with Lama 3. [00:15:00] 3 launched, they only launched the 70B because they use 4 or 5B to distill the 70B.[00:15:03] swyx: So I don't know if like open source is keeping up. I think they're the, the open source industrial complex is very invested in telling you that the, if the gap is narrowing, I kind of disagree. I think that the gap is widening with O1. I think there are very, very smart people trying to narrow that gap and they should.[00:15:22] swyx: I really wish them success, but you cannot use a chart that is nearing 100 in your saturation chart. And look, the distance between open source and closed source is narrowing. Of course it's going to narrow because you're near 100. This is stupid. But in metrics that matter, is open source narrowing?[00:15:38] swyx: Probably not for O1 for a while. And it's really up to the open source guys to figure out if they can match O1 or not.[00:15:46] Alessio: I think inference time compute is bad for open source just because, you know, Doc can donate the flops at training time, but he cannot donate the flops at inference time. So it's really hard to like actually keep up on that axis.[00:15:59] Alessio: Big, big business [00:16:00] model shift. So I don't know what that means for the GPU clouds. I don't know what that means for the hyperscalers, but obviously the big labs have a lot of advantage. Because, like, it's not a static artifact that you're putting the compute in. You're kind of doing that still, but then you're putting a lot of computed inference too.[00:16:17] swyx: Yeah, yeah, yeah. Um, I mean, Llama4 will be reasoning oriented. We talked with Thomas Shalom. Um, kudos for getting that episode together. That was really nice. Good, well timed. Actually, I connected with the AI meta guy, uh, at NeurIPS, and, um, yeah, we're going to coordinate something for Llama4. Yeah, yeah,[00:16:32] Alessio: and our friend, yeah.[00:16:33] Alessio: Clara Shi just joined to lead the business agent side. So I'm sure we'll have her on in the new year.[00:16:39] swyx: Yeah. So, um, my comment on, on the business model shift, this is super interesting. Apparently it is wide knowledge that OpenAI wanted more than 6. 6 billion dollars for their fundraise. They wanted to raise, you know, higher, and they did not.[00:16:51] swyx: And what that means is basically like, it's very convenient that we're not getting GPT 5, which would have been a larger pre train. We should have a lot of upfront money. And [00:17:00] instead we're, we're converting fixed costs into variable costs, right. And passing it on effectively to the customer. And it's so much easier to take margin there because you can directly attribute it to like, Oh, you're using this more.[00:17:12] swyx: Therefore you, you pay more of the cost and I'll just slap a margin in there. So like that lets you control your growth margin and like tie your. Your spend, or your sort of inference spend, accordingly. And it's just really interesting to, that this change in the sort of inference paradigm has arrived exactly at the same time that the funding environment for pre training is effectively drying up, kind of.[00:17:36] swyx: I feel like maybe the VCs are very in tune with research anyway, so like, they would have noticed this, but, um, it's just interesting.[00:17:43] Alessio: Yeah, and I was looking back at our yearly recap of last year. Yeah. And the big thing was like the mixed trial price fights, you know, and I think now it's almost like there's nowhere to go, like, you know, Gemini Flash is like basically giving it away for free.[00:17:55] Alessio: So I think this is a good way for the labs to generate more revenue and pass down [00:18:00] some of the compute to the customer. I think they're going to[00:18:02] swyx: keep going. I think that 2, will come.[00:18:05] Alessio: Yeah, I know. Totally. I mean, next year, the first thing I'm doing is signing up for Devin. Signing up for the pro chat GBT.[00:18:12] Alessio: Just to try. I just want to see what does it look like to spend a thousand dollars a month on AI?[00:18:17] swyx: Yes. Yes. I think if your, if your, your job is a, at least AI content creator or VC or, you know, someone who, whose job it is to stay on, stay on top of things, you should already be spending like a thousand dollars a month on, on stuff.[00:18:28] swyx: And then obviously easy to spend, hard to use. You have to actually use. The good thing is that actually Google lets you do a lot of stuff for free now. So like deep research. That they just launched. Uses a ton of inference and it's, it's free while it's in preview.[00:18:45] Alessio: Yeah. They need to put that in Lindy.[00:18:47] Alessio: I've been using Lindy lately. I've been a built a bunch of things once we had flow because I liked the new thing. It's pretty good. I even did a phone call assistant. Um, yeah, they just launched Lindy voice. Yeah, I think once [00:19:00] they get advanced voice mode like capability today, still like speech to text, you can kind of tell.[00:19:06] Alessio: Um, but it's good for like reservations and things like that. So I have a meeting prepper thing. And so[00:19:13] swyx: it's good. Okay. I feel like we've, we've covered a lot of stuff. Uh, I, yeah, I, you know, I think We will go over the individual, uh, talks in a separate episode. Uh, I don't want to take too much time with, uh, this stuff, but that suffice to say that there is a lot of progress in each field.[00:19:28] swyx: Uh, we covered vision. Basically this is all like the audience voting for what they wanted. And then I just invited the best people I could find in each audience, especially agents. Um, Graham, who I talked to at ICML in Vienna, he is currently still number one. It's very hard to stay on top of SweetBench.[00:19:45] swyx: OpenHand is currently still number one. switchbench full, which is the hardest one. He had very good thoughts on agents, which I, which I'll highlight for people. Everyone is saying 2025 is the year of agents, just like they said last year. And, uh, but he had [00:20:00] thoughts on like eight parts of what are the frontier problems to solve in agents.[00:20:03] swyx: And so I'll highlight that talk as well.[00:20:05] Alessio: Yeah. The number six, which is the Hacken agents learn more about the environment, has been a Super interesting to us as well, just to think through, because, yeah, how do you put an agent in an enterprise where most things in an enterprise have never been public, you know, a lot of the tooling, like the code bases and things like that.[00:20:23] Alessio: So, yeah, there's not indexing and reg. Well, yeah, but it's more like. You can't really rag things that are not documented. But people know them based on how they've been doing it. You know, so I think there's almost this like, you know, Oh, institutional knowledge. Yeah, the boring word is kind of like a business process extraction.[00:20:38] Alessio: Yeah yeah, I see. It's like, how do you actually understand how these things are done? I see. Um, and I think today the, the problem is that, Yeah, the agents are, that most people are building are good at following instruction, but are not as good as like extracting them from you. Um, so I think that will be a big unlock just to touch quickly on the Jeff Dean thing.[00:20:55] Alessio: I thought it was pretty, I mean, we'll link it in the, in the things, but. I think the main [00:21:00] focus was like, how do you use ML to optimize the systems instead of just focusing on ML to do something else? Yeah, I think speculative decoding, we had, you know, Eugene from RWKB on the podcast before, like he's doing a lot of that with Fetterless AI.[00:21:12] swyx: Everyone is. I would say it's the norm. I'm a little bit uncomfortable with how much it costs, because it does use more of the GPU per call. But because everyone is so keen on fast inference, then yeah, makes sense.[00:21:24] Alessio: Exactly. Um, yeah, but we'll link that. Obviously Jeff is great.[00:21:30] swyx: Jeff is, Jeff's talk was more, it wasn't focused on Gemini.[00:21:33] swyx: I think people got the wrong impression from my tweet. It's more about how Google approaches ML and uses ML to design systems and then systems feedback into ML. And I think this ties in with Lubna's talk.[00:21:45] Synthetic Data and Future Trends[00:21:45] swyx: on synthetic data where it's basically the story of bootstrapping of humans and AI in AI research or AI in production.[00:21:53] swyx: So her talk was on synthetic data, where like how much synthetic data has grown in 2024 in the pre training side, the post training side, [00:22:00] and the eval side. And I think Jeff then also extended it basically to chips, uh, to chip design. So he'd spend a lot of time talking about alpha chip. And most of us in the audience are like, we're not working on hardware, man.[00:22:11] swyx: Like you guys are great. TPU is great. Okay. We'll buy TPUs.[00:22:14] Alessio: And then there was the earlier talk. Yeah. But, and then we have, uh, I don't know if we're calling them essays. What are we calling these? But[00:22:23] swyx: for me, it's just like bonus for late in space supporters, because I feel like they haven't been getting anything.[00:22:29] swyx: And then I wanted a more high frequency way to write stuff. Like that one I wrote in an afternoon. I think basically we now have an answer to what Ilya saw. It's one year since. The blip. And we know what he saw in 2014. We know what he saw in 2024. We think we know what he sees in 2024. He gave some hints and then we have vague indications of what he saw in 2023.[00:22:54] swyx: So that was the Oh, and then 2016 as well, because of this lawsuit with Elon, OpenAI [00:23:00] is publishing emails from Sam's, like, his personal text messages to Siobhan, Zelis, or whatever. So, like, we have emails from Ilya saying, this is what we're seeing in OpenAI, and this is why we need to scale up GPUs. And I think it's very prescient in 2016 to write that.[00:23:16] swyx: And so, like, it is exactly, like, basically his insights. It's him and Greg, basically just kind of driving the scaling up of OpenAI, while they're still playing Dota. They're like, no, like, we see the path here.[00:23:30] Alessio: Yeah, and it's funny, yeah, they even mention, you know, we can only train on 1v1 Dota. We need to train on 5v5, and that takes too many GPUs.[00:23:37] Alessio: Yeah,[00:23:37] swyx: and at least for me, I can speak for myself, like, I didn't see the path from Dota to where we are today. I think even, maybe if you ask them, like, they wouldn't necessarily draw a straight line. Yeah,[00:23:47] Alessio: no, definitely. But I think like that was like the whole idea of almost like the RL and we talked about this with Nathan on his podcast.[00:23:55] Alessio: It's like with RL, you can get very good at specific things, but then you can't really like generalize as much. And I [00:24:00] think the language models are like the opposite, which is like, you're going to throw all this data at them and scale them up, but then you really need to drive them home on a specific task later on.[00:24:08] Alessio: And we'll talk about the open AI reinforcement, fine tuning, um, announcement too, and all of that. But yeah, I think like scale is all you need. That's kind of what Elia will be remembered for. And I think just maybe to clarify on like the pre training is over thing that people love to tweet. I think the point of the talk was like everybody, we're scaling these chips, we're scaling the compute, but like the second ingredient which is data is not scaling at the same rate.[00:24:35] Alessio: So it's not necessarily pre training is over. It's kind of like What got us here won't get us there. In his email, he predicted like 10x growth every two years or something like that. And I think maybe now it's like, you know, you can 10x the chips again, but[00:24:49] swyx: I think it's 10x per year. Was it? I don't know.[00:24:52] Alessio: Exactly. And Moore's law is like 2x. So it's like, you know, much faster than that. And yeah, I like the fossil fuel of AI [00:25:00] analogy. It's kind of like, you know, the little background tokens thing. So the OpenAI reinforcement fine tuning is basically like, instead of fine tuning on data, you fine tune on a reward model.[00:25:09] Alessio: So it's basically like, instead of being data driven, it's like task driven. And I think people have tasks to do, they don't really have a lot of data. So I'm curious to see how that changes, how many people fine tune, because I think this is what people run into. It's like, Oh, you can fine tune llama. And it's like, okay, where do I get the data?[00:25:27] Alessio: To fine tune it on, you know, so it's great that we're moving the thing. And then I really like he had this chart where like, you know, the brain mass and the body mass thing is basically like mammals that scaled linearly by brain and body size, and then humans kind of like broke off the slope. So it's almost like maybe the mammal slope is like the pre training slope.[00:25:46] Alessio: And then the post training slope is like the, the human one.[00:25:49] swyx: Yeah. I wonder what the. I mean, we'll know in 10 years, but I wonder what the y axis is for, for Ilya's SSI. We'll try to get them on.[00:25:57] Alessio: Ilya, if you're listening, you're [00:26:00] welcome here. Yeah, and then he had, you know, what comes next, like agent, synthetic data, inference, compute, I thought all of that was like that.[00:26:05] Alessio: I don't[00:26:05] swyx: think he was dropping any alpha there. Yeah, yeah, yeah.[00:26:07] Alessio: Yeah. Any other new reps? Highlights?[00:26:10] swyx: I think that there was comparatively a lot more work. Oh, by the way, I need to plug that, uh, my friend Yi made this, like, little nice paper. Yeah, that was really[00:26:20] swyx: nice.[00:26:20] swyx: Uh, of, uh, of, like, all the, he's, she called it must read papers of 2024.[00:26:26] swyx: So I laid out some of these at NeurIPS, and it was just gone. Like, everyone just picked it up. Because people are dying for, like, little guidance and visualizations And so, uh, I thought it was really super nice that we got there.[00:26:38] Alessio: Should we do a late in space book for each year? Uh, I thought about it. For each year we should.[00:26:42] Alessio: Coffee table book. Yeah. Yeah. Okay. Put it in the will. Hi, Will. By the way, we haven't introduced you. He's our new, you know, general organist, Jamie. You need to[00:26:52] swyx: pull up more things. One thing I saw that, uh, Okay, one fun one, and then one [00:27:00] more general one. So the fun one is this paper on agent collusion. This is a paper on steganography.[00:27:06] swyx: This is secret collusion among AI agents, multi agent deception via steganography. I tried to go to NeurIPS in order to find these kinds of papers because the real reason Like NeurIPS this year has a lottery system. A lot of people actually even go and don't buy tickets because they just go and attend the side events.[00:27:22] swyx: And then also the people who go and end up crowding around the most popular papers, which you already know and already read them before you showed up to NeurIPS. So the only reason you go there is to talk to the paper authors, but there's like something like 10, 000 other. All these papers out there that, you know, are just people's work that they, that they did on the air and they failed to get attention for one reason or another.[00:27:42] swyx: And this was one of them. Uh, it was like all the way at the back. And this is a deep mind paper that actually focuses on collusion between AI agents, uh, by hiding messages in the text that they generate. Uh, so that's what steganography is. So a very simple example would be the first letter of every word.[00:27:57] swyx: If you Pick that out, you know, and the code sends a [00:28:00] different message than that. But something I've always emphasized is to LLMs, we read left to right. LLMs can read up, down, sideways, you know, in random character order. And it's the same to them as it is to us. So if we were ever to get You know, self motivated, underlined LLMs that we're trying to collaborate to take over the planet.[00:28:19] swyx: This would be how they do it. They spread messages among us in the messages that we generate. And he developed a scaling law for that. So he marked, I'm showing it on screen right now, the emergence of this phenomenon. Basically, for example, for Cypher encoding, GPT 2, Lama 2, mixed trial, GPT 3. 5, zero capabilities, and sudden 4.[00:28:40] swyx: And this is the kind of Jason Wei type emergence properties that people kind of look for. I think what made this paper stand out as well, so he developed the benchmark for steganography collusion, and he also focused on shelling point collusion, which is very low coordination. For agreeing on a decoding encoding format, you kind of need to have some [00:29:00] agreement on that.[00:29:00] swyx: But, but shelling point means like very, very low or almost no coordination. So for example, if I, if I ask someone, if the only message I give you is meet me in New York and you're not aware. Or when you would probably meet me at Grand Central Station. That is the Grand Central Station is a shelling point.[00:29:16] swyx: And it's probably somewhere, somewhere during the day. That is the shelling point of New York is Grand Central. To that extent, shelling points for steganography are things like the, the, the common decoding methods that we talked about. It will be interesting at some point in the future when we are worried about alignment.[00:29:30] swyx: It is not interesting today, but it's interesting that DeepMind is already thinking about this.[00:29:36] Alessio: I think that's like one of the hardest things about NeurIPS. It's like the long tail. I[00:29:41] swyx: found a pricing guy. I'm going to feature him on the podcast. Basically, this guy from NVIDIA worked out the optimal pricing for language models.[00:29:51] swyx: It's basically an econometrics paper at NeurIPS, where everyone else is talking about GPUs. And the guy with the GPUs is[00:29:57] Alessio: talking[00:29:57] swyx: about economics instead. [00:30:00] That was the sort of fun one. So the focus I saw is that model papers at NeurIPS are kind of dead. No one really presents models anymore. It's just data sets.[00:30:12] swyx: This is all the grad students are working on. So like there was a data sets track and then I was looking around like, I was like, you don't need a data sets track because every paper is a data sets paper. And so data sets and benchmarks, they're kind of flip sides of the same thing. So Yeah. Cool. Yeah, if you're a grad student, you're a GPU boy, you kind of work on that.[00:30:30] swyx: And then the, the sort of big model that people walk around and pick the ones that they like, and then they use it in their models. And that's, that's kind of how it develops. I, I feel like, um, like, like you didn't last year, you had people like Hao Tian who worked on Lava, which is take Lama and add Vision.[00:30:47] swyx: And then obviously actually I hired him and he added Vision to Grok. Now he's the Vision Grok guy. This year, I don't think there was any of those.[00:30:55] Alessio: What were the most popular, like, orals? Last year it was like the [00:31:00] Mixed Monarch, I think, was like the most attended. Yeah, uh, I need to look it up. Yeah, I mean, if nothing comes to mind, that's also kind of like an answer in a way.[00:31:10] Alessio: But I think last year there was a lot of interest in, like, furthering models and, like, different architectures and all of that.[00:31:16] swyx: I will say that I felt the orals, oral picks this year were not very good. Either that or maybe it's just a So that's the highlight of how I have changed in terms of how I view papers.[00:31:29] swyx: So like, in my estimation, two of the best papers in this year for datasets or data comp and refined web or fine web. These are two actually industrially used papers, not highlighted for a while. I think DCLM got the spotlight, FineWeb didn't even get the spotlight. So like, it's just that the picks were different.[00:31:48] swyx: But one thing that does get a lot of play that a lot of people are debating is the role that's scheduled. This is the schedule free optimizer paper from Meta from Aaron DeFazio. And this [00:32:00] year in the ML community, there's been a lot of chat about shampoo, soap, all the bathroom amenities for optimizing your learning rates.[00:32:08] swyx: And, uh, most people at the big labs are. Who I asked about this, um, say that it's cute, but it's not something that matters. I don't know, but it's something that was discussed and very, very popular. 4Wars[00:32:19] Alessio: of AI recap maybe, just quickly. Um, where do you want to start? Data?[00:32:26] swyx: So to remind people, this is the 4Wars piece that we did as one of our earlier recaps of this year.[00:32:31] swyx: And the belligerents are on the left, journalists, writers, artists, anyone who owns IP basically, New York Times, Stack Overflow, Reddit, Getty, Sarah Silverman, George RR Martin. Yeah, and I think this year we can add Scarlett Johansson to that side of the fence. So anyone suing, open the eye, basically. I actually wanted to get a snapshot of all the lawsuits.[00:32:52] swyx: I'm sure some lawyer can do it. That's the data quality war. On the right hand side, we have the synthetic data people, and I think we talked about Lumna's talk, you know, [00:33:00] really showing how much synthetic data has come along this year. I think there was a bit of a fight between scale. ai and the synthetic data community, because scale.[00:33:09] swyx: ai published a paper saying that synthetic data doesn't work. Surprise, surprise, scale. ai is the leading vendor of non synthetic data. Only[00:33:17] Alessio: cage free annotated data is useful.[00:33:21] swyx: So I think there's some debate going on there, but I don't think it's much debate anymore that at least synthetic data, for the reasons that are blessed in Luna's talk, Makes sense.[00:33:32] swyx: I don't know if you have any perspectives there.[00:33:34] Alessio: I think, again, going back to the reinforcement fine tuning, I think that will change a little bit how people think about it. I think today people mostly use synthetic data, yeah, for distillation and kind of like fine tuning a smaller model from like a larger model.[00:33:46] Alessio: I'm not super aware of how the frontier labs use it outside of like the rephrase, the web thing that Apple also did. But yeah, I think it'll be. Useful. I think like whether or not that gets us the big [00:34:00] next step, I think that's maybe like TBD, you know, I think people love talking about data because it's like a GPU poor, you know, I think, uh, synthetic data is like something that people can do, you know, so they feel more opinionated about it compared to, yeah, the optimizers stuff, which is like,[00:34:17] swyx: they don't[00:34:17] Alessio: really work[00:34:18] swyx: on.[00:34:18] swyx: I think that there is an angle to the reasoning synthetic data. So this year, we covered in the paper club, the star series of papers. So that's star, Q star, V star. It basically helps you to synthesize reasoning steps, or at least distill reasoning steps from a verifier. And if you look at the OpenAI RFT, API that they released, or that they announced, basically they're asking you to submit graders, or they choose from a preset list of graders.[00:34:49] swyx: Basically It feels like a way to create valid synthetic data for them to fine tune their reasoning paths on. Um, so I think that is another angle where it starts to make sense. And [00:35:00] so like, it's very funny that basically all the data quality wars between Let's say the music industry or like the newspaper publishing industry or the textbooks industry on the big labs.[00:35:11] swyx: It's all of the pre training era. And then like the new era, like the reasoning era, like nobody has any problem with all the reasoning, especially because it's all like sort of math and science oriented with, with very reasonable graders. I think the more interesting next step is how does it generalize beyond STEM?[00:35:27] swyx: We've been using O1 for And I would say like for summarization and creative writing and instruction following, I think it's underrated. I started using O1 in our intro songs before we killed the intro songs, but it's very good at writing lyrics. You know, I can actually say like, I think one of the O1 pro demos.[00:35:46] swyx: All of these things that Noam was showing was that, you know, you can write an entire paragraph or three paragraphs without using the letter A, right?[00:35:53] Creative Writing with AI[00:35:53] swyx: So like, like literally just anything instead of token, like not even token level, character level manipulation and [00:36:00] counting and instruction following. It's, uh, it's very, very strong.[00:36:02] swyx: And so no surprises when I ask it to rhyme, uh, and to, to create song lyrics, it's going to do that very much better than in previous models. So I think it's underrated for creative writing.[00:36:11] Alessio: Yeah.[00:36:12] Legal and Ethical Issues in AI[00:36:12] Alessio: What do you think is the rationale that they're going to have in court when they don't show you the thinking traces of O1, but then they want us to, like, they're getting sued for using other publishers data, you know, but then on their end, they're like, well, you shouldn't be using my data to then train your model.[00:36:29] Alessio: So I'm curious to see how that kind of comes. Yeah, I mean, OPA has[00:36:32] swyx: many ways to publish, to punish people without bringing, taking them to court. Already banned ByteDance for distilling their, their info. And so anyone caught distilling the chain of thought will be just disallowed to continue on, on, on the API.[00:36:44] swyx: And it's fine. It's no big deal. Like, I don't even think that's an issue at all, just because the chain of thoughts are pretty well hidden. Like you have to work very, very hard to, to get it to leak. And then even when it leaks the chain of thought, you don't know if it's, if it's [00:37:00] The bigger concern is actually that there's not that much IP hiding behind it, that Cosign, which we talked about, we talked to him on Dev Day, can just fine tune 4.[00:37:13] swyx: 0 to beat 0. 1 Cloud SONET so far is beating O1 on coding tasks without, at least O1 preview, without being a reasoning model, same for Gemini Pro or Gemini 2. 0. So like, how much is reasoning important? How much of a moat is there in this, like, All of these are proprietary sort of training data that they've presumably accomplished.[00:37:34] swyx: Because even DeepSeek was able to do it. And they had, you know, two months notice to do this, to do R1. So, it's actually unclear how much moat there is. Obviously, you know, if you talk to the Strawberry team, they'll be like, yeah, I mean, we spent the last two years doing this. So, we don't know. And it's going to be Interesting because there'll be a lot of noise from people who say they have inference time compute and actually don't because they just have fancy chain of thought.[00:38:00][00:38:00] swyx: And then there's other people who actually do have very good chain of thought. And you will not see them on the same level as OpenAI because OpenAI has invested a lot in building up the mythology of their team. Um, which makes sense. Like the real answer is somewhere in between.[00:38:13] Alessio: Yeah, I think that's kind of like the main data war story developing.[00:38:18] The Data War: GPU Poor vs. GPU Rich[00:38:18] Alessio: GPU poor versus GPU rich. Yeah. Where do you think we are? I think there was, again, going back to like the small model thing, there was like a time in which the GPU poor were kind of like the rebel faction working on like these models that were like open and small and cheap. And I think today people don't really care as much about GPUs anymore.[00:38:37] Alessio: You also see it in the price of the GPUs. Like, you know, that market is kind of like plummeted because there's people don't want to be, they want to be GPU free. They don't even want to be poor. They just want to be, you know, completely without them. Yeah. How do you think about this war? You[00:38:52] swyx: can tell me about this, but like, I feel like the, the appetite for GPU rich startups, like the, you know, the, the funding plan is we will raise 60 million and [00:39:00] we'll give 50 of that to NVIDIA.[00:39:01] swyx: That is gone, right? Like, no one's, no one's pitching that. This was literally the plan, the exact plan of like, I can name like four or five startups, you know, this time last year. So yeah, GPU rich startups gone.[00:39:12] The Rise of GPU Ultra Rich[00:39:12] swyx: But I think like, The GPU ultra rich, the GPU ultra high net worth is still going. So, um, now we're, you know, we had Leopold's essay on the trillion dollar cluster.[00:39:23] swyx: We're not quite there yet. We have multiple labs, um, you know, XAI very famously, you know, Jensen Huang praising them for being. Best boy number one in spinning up 100, 000 GPU cluster in like 12 days or something. So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.[00:39:46] swyx: Like you don't even know what it's going to, what you're going to use it for. You just, you just need it. And it makes sense that if, especially if we're going into. More researchy territory than we are. So let's say 2020 to 2023 was [00:40:00] let's scale big models territory because we had GPT 3 in 2020 and we were like, okay, we'll go from 1.[00:40:05] swyx: 75b to 1. 8b, 1. 8t. And that was GPT 3 to GPT 4. Okay, that's done. As far as everyone is concerned, Opus 3. 5 is not coming out, GPT 4. 5 is not coming out, and Gemini 2, we don't have Pro, whatever. We've hit that wall. Maybe I'll call it the 2 trillion perimeter wall. We're not going to 10 trillion. No one thinks it's a good idea, at least from training costs, from the amount of data, or at least the inference.[00:40:36] swyx: Would you pay 10x the price of GPT Probably not. Like, like you want something else that, that is at least more useful. So it makes sense that people are pivoting in terms of their inference paradigm.[00:40:47] Emerging Trends in AI Models[00:40:47] swyx: And so when it's more researchy, then you actually need more just general purpose compute to mess around with, uh, at the exact same time that production deployments of the old, the previous paradigm is still ramping up,[00:40:58] swyx: um,[00:40:58] swyx: uh, pretty aggressively.[00:40:59] swyx: So [00:41:00] it makes sense that the GPU rich are growing. We have now interviewed both together and fireworks and replicates. Uh, we haven't done any scale yet. But I think Amazon, maybe kind of a sleeper one, Amazon, in a sense of like they, at reInvent, I wasn't expecting them to do so well, but they are now a foundation model lab.[00:41:18] swyx: It's kind of interesting. Um, I think, uh, you know, David went over there and started just creating models.[00:41:25] Alessio: Yeah, I mean, that's the power of prepaid contracts. I think like a lot of AWS customers, you know, they do this big reserve instance contracts and now they got to use their money. That's why so many startups.[00:41:37] Alessio: Get bought through the AWS marketplace so they can kind of bundle them together and prefer pricing.[00:41:42] swyx: Okay, so maybe GPU super rich doing very well, GPU middle class dead, and then GPU[00:41:48] Alessio: poor. I mean, my thing is like, everybody should just be GPU rich. There shouldn't really be, even the GPU poorest, it's like, does it really make sense to be GPU poor?[00:41:57] Alessio: Like, if you're GPU poor, you should just use the [00:42:00] cloud. Yes, you know, and I think there might be a future once we kind of like figure out what the size and shape of these models is where like the tiny box and these things come to fruition where like you can be GPU poor at home. But I think today is like, why are you working so hard to like get these models to run on like very small clusters where it's like, It's so cheap to run them.[00:42:21] Alessio: Yeah, yeah,[00:42:22] swyx: yeah. I think mostly people think it's cool. People think it's a stepping stone to scaling up. So they aspire to be GPU rich one day and they're working on new methods. Like news research, like probably the most deep tech thing they've done this year is Distro or whatever the new name is.[00:42:38] swyx: There's a lot of interest in heterogeneous computing, distributed computing. I tend generally to de emphasize that historically, but it may be coming to a time where it is starting to be relevant. I don't know. You know, SF compute launched their compute marketplace this year, and like, who's really using that?[00:42:53] swyx: Like, it's a bunch of small clusters, disparate types of compute, and if you can make that [00:43:00] useful, then that will be very beneficial to the broader community, but maybe still not the source of frontier models. It's just going to be a second tier of compute that is unlocked for people, and that's fine. But yeah, I mean, I think this year, I would say a lot more on device, We are, I now have Apple intelligence on my phone.[00:43:19] swyx: Doesn't do anything apart from summarize my notifications. But still, not bad. Like, it's multi modal.[00:43:25] Alessio: Yeah, the notification summaries are so and so in my experience.[00:43:29] swyx: Yeah, but they add, they add juice to life. And then, um, Chrome Nano, uh, Gemini Nano is coming out in Chrome. Uh, they're still feature flagged, but you can, you can try it now if you, if you use the, uh, the alpha.[00:43:40] swyx: And so, like, I, I think, like, you know, We're getting the sort of GPU poor version of a lot of these things coming out, and I think it's like quite useful. Like Windows as well, rolling out RWKB in sort of every Windows department is super cool. And I think the last thing that I never put in this GPU poor war, that I think I should now, [00:44:00] is the number of startups that are GPU poor but still scaling very well, as sort of wrappers on top of either a foundation model lab, or GPU Cloud.[00:44:10] swyx: GPU Cloud, it would be Suno. Suno, Ramp has rated as one of the top ranked, fastest growing startups of the year. Um, I think the last public number is like zero to 20 million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on Moto, uh, who we've also talked to on, on the podcast.[00:44:31] swyx: The other one would be Bolt, straight cloud wrapper. And, and, um, Again, another, now they've announced 20 million ARR, which is another step up from our 8 million that we put on the title. So yeah, I mean, it's crazy that all these GPU pores are finding a way while the GPU riches are also finding a way. And then the only failures, I kind of call this the GPU smiling curve, where the edges do well, because you're either close to the machines, and you're like [00:45:00] number one on the machines, or you're like close to the customers, and you're number one on the customer side.[00:45:03] swyx: And the people who are in the middle. Inflection, um, character, didn't do that great. I think character did the best of all of them. Like, you have a note in here that we apparently said that character's price tag was[00:45:15] Alessio: 1B.[00:45:15] swyx: Did I say that?[00:45:16] Alessio: Yeah. You said Google should just buy them for 1B. I thought it was a crazy number.[00:45:20] Alessio: Then they paid 2. 7 billion. I mean, for like,[00:45:22] swyx: yeah.[00:45:22] Alessio: What do you pay for node? Like, I don't know what the game world was like. Maybe the starting price was 1B. I mean, whatever it was, it worked out for everybody involved.[00:45:31] The Multi-Modality War[00:45:31] Alessio: Multimodality war. And this one, we never had text to video in the first version, which now is the hottest.[00:45:37] swyx: Yeah, I would say it's a subset of image, but yes.[00:45:40] Alessio: Yeah, well, but I think at the time it wasn't really something people were doing, and now we had VO2 just came out yesterday. Uh, Sora was released last month, last week. I've not tried Sora, because the day that I tried, it wasn't, yeah. I[00:45:54] swyx: think it's generally available now, you can go to Sora.[00:45:56] swyx: com and try it. Yeah, they had[00:45:58] Alessio: the outage. Which I [00:46:00] think also played a part into it. Small things. Yeah. What's the other model that you posted today that was on Replicate? Video or OneLive?[00:46:08] swyx: Yeah. Very, very nondescript name, but it is from Minimax, which I think is a Chinese lab. The Chinese labs do surprisingly well at the video models.[00:46:20] swyx: I'm not sure it's actually Chinese. I don't know. Hold me up to that. Yep. China. It's good. Yeah, the Chinese love video. What can I say? They have a lot of training data for video. Or a more relaxed regulatory environment.[00:46:37] Alessio: Uh, well, sure, in some way. Yeah, I don't think there's much else there. I think like, you know, on the image side, I think it's still open.[00:46:45] Alessio: Yeah, I mean,[00:46:46] swyx: 11labs is now a unicorn. So basically, what is multi modality war? Multi modality war is, do you specialize in a single modality, right? Or do you have GodModel that does all the modalities? So this is [00:47:00] definitely still going, in a sense of 11 labs, you know, now Unicorn, PicoLabs doing well, they launched Pico 2.[00:47:06] swyx: 0 recently, HeyGen, I think has reached 100 million ARR, Assembly, I don't know, but they have billboards all over the place, so I assume they're doing very, very well. So these are all specialist models, specialist models and specialist startups. And then there's the big labs who are doing the sort of all in one play.[00:47:24] swyx: And then here I would highlight Gemini 2 for having native image output. Have you seen the demos? Um, yeah, it's, it's hard to keep up. Literally they launched this last week and a shout out to Paige Bailey, who came to the Latent Space event to demo on the day of launch. And she wasn't prepared. She was just like, I'm just going to show you.[00:47:43] swyx: So they have voice. They have, you know, obviously image input, and then they obviously can code gen and all that. But the new one that OpenAI and Meta both have but they haven't launched yet is image output. So you can literally, um, I think their demo video was that you put in an image of a [00:48:00] car, and you ask for minor modifications to that car.[00:48:02] swyx: They can generate you that modification exactly as you asked. So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there in paint there and all that, all that stuff. This is small model nonsense. Big model people are like, huh, we got you in as everything in the transformer.[00:48:21] swyx: This is the multimodality war, which is, do you, do you bet on the God model or do you string together a whole bunch of, uh, Small models like a, like a chump. Yeah,[00:48:29] Alessio: I don't know, man. Yeah, that would be interesting. I mean, obviously I use Midjourney for all of our thumbnails. Um, they've been doing a ton on the product, I would say.[00:48:38] Alessio: They launched a new Midjourney editor thing. They've been doing a ton. Because I think, yeah, the motto is kind of like, Maybe, you know, people say black forest, the black forest models are better than mid journey on a pixel by pixel basis. But I think when you put it, put it together, have you tried[00:48:53] swyx: the same problems on black forest?[00:48:55] Alessio: Yes. But the problem is just like, you know, on black forest, it generates one image. And then it's like, you got to [00:49:00] regenerate. You don't have all these like UI things. Like what I do, no, but it's like time issue, you know, it's like a mid[00:49:06] swyx: journey. Call the API four times.[00:49:08] Alessio: No, but then there's no like variate.[00:49:10] Alessio: Like the good thing about mid journey is like, you just go in there and you're cooking. There's a lot of stuff that just makes it really easy. And I think people underestimate that. Like, it's not really a skill issue, because I'm paying mid journey, so it's a Black Forest skill issue, because I'm not paying them, you know?[00:49:24] Alessio: Yeah,[00:49:25] swyx: so, okay, so, uh, this is a UX thing, right? Like, you, you, you understand that, at least, we think that Black Forest should be able to do all that stuff. I will also shout out, ReCraft has come out, uh, on top of the image arena that, uh, artificial analysis has done, has apparently, uh, Flux's place. Is this still true?[00:49:41] swyx: So, Artificial Analysis is now a company. I highlighted them I think in one of the early AI Newses of the year. And they have launched a whole bunch of arenas. So, they're trying to take on LM Arena, Anastasios and crew. And they have an image arena. Oh yeah, Recraft v3 is now beating Flux 1. 1. Which is very surprising [00:50:00] because Flux And Black Forest Labs are the old stable diffusion crew who left stability after, um, the management issues.[00:50:06] swyx: So Recurve has come from nowhere to be the top image model. Uh, very, very strange. I would also highlight that Grok has now launched Aurora, which is, it's very interesting dynamics between Grok and Black Forest Labs because Grok's images were originally launched, uh, in partnership with Black Forest Labs as a, as a thin wrapper.[00:50:24] swyx: And then Grok was like, no, we'll make our own. And so they've made their own. I don't know, there are no APIs or benchmarks about it. They just announced it. So yeah, that's the multi modality war. I would say that so far, the small model, the dedicated model people are winning, because they are just focused on their tasks.[00:50:42] swyx: But the big model, People are always catching up. And the moment I saw the Gemini 2 demo of image editing, where I can put in an image and just request it and it does, that's how AI should work. Not like a whole bunch of complicated steps. So it really is something. And I think one frontier that we haven't [00:51:00] seen this year, like obviously video has done very well, and it will continue to grow.[00:51:03] swyx: You know, we only have Sora Turbo today, but at some point we'll get full Sora. Oh, at least the Hollywood Labs will get Fulsora. We haven't seen video to audio, or video synced to audio. And so the researchers that I talked to are already starting to talk about that as the next frontier. But there's still maybe like five more years of video left to actually be Soda.[00:51:23] swyx: I would say that Gemini's approach Compared to OpenAI, Gemini seems, or DeepMind's approach to video seems a lot more fully fledged than OpenAI. Because if you look at the ICML recap that I published that so far nobody has listened to, um, that people have listened to it. It's just a different, definitely different audience.[00:51:43] swyx: It's only seven hours long. Why are people not listening? It's like everything in Uh, so, so DeepMind has, is working on Genie. They also launched Genie 2 and VideoPoet. So, like, they have maybe four years advantage on world modeling that OpenAI does not have. Because OpenAI basically only started [00:52:00] Diffusion Transformers last year, you know, when they hired, uh, Bill Peebles.[00:52:03] swyx: So, DeepMind has, has a bit of advantage here, I would say, in, in, in showing, like, the reason that VO2, while one, They cherry pick their videos. So obviously it looks better than Sora, but the reason I would believe that VO2, uh, when it's fully launched will do very well is because they have all this background work in video that they've done for years.[00:52:22] swyx: Like, like last year's NeurIPS, I already was interviewing some of their video people. I forget their model name, but for, for people who are dedicated fans, they can go to NeurIPS 2023 and see, see that paper.[00:52:32] Alessio: And then last but not least, the LLMOS. We renamed it to Ragops, formerly known as[00:52:39] swyx: Ragops War. I put the latest chart on the Braintrust episode.[00:52:43] swyx: I think I'm going to separate these essays from the episode notes. So the reason I used to do that, by the way, is because I wanted to show up on Hacker News. I wanted the podcast to show up on Hacker News. So I always put an essay inside of there because Hacker News people like to read and not listen.[00:52:58] Alessio: So episode essays,[00:52:59] swyx: I remember [00:53:00] purchasing them separately. You say Lanchain Llama Index is still growing.[00:53:03] Alessio: Yeah, so I looked at the PyPy stats, you know. I don't care about stars. On PyPy you see Do you want to share your screen? Yes. I prefer to look at actual downloads, not at stars on GitHub. So if you look at, you know, Lanchain still growing.[00:53:20] Alessio: These are the last six months. Llama Index still growing. What I've basically seen is like things that, One, obviously these things have A commercial product. So there's like people buying this and sticking with it versus kind of hopping in between things versus, you know, for example, crew AI, not really growing as much.[00:53:38] Alessio: The stars are growing. If you look on GitHub, like the stars are growing, but kind of like the usage is kind of like flat. In the last six months, have they done some[00:53:4

Tell us what you think about this podcast!Understanding the biblical foundation and structure of church leadership is essential for every pastor. This lesson explores the roles of pastors, elders, and deacons, emphasizing order, accountability, and the Apostolic Pentecostal approach to leading a church according to scriptural principles.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Tell us what you think about this podcast!Understanding the biblical foundation and structure of church leadership is essential for every pastor. This lesson explores the roles of pastors, elders, and deacons, emphasizing order, accountability, and the Apostolic Pentecostal approach to leading a church according to scriptural principles.For more lessons and sermons, follow our YouTube channel at https://www.youtube.com/@GBT

Send Everyday AI and Jordan a text messageThere's very few people in the world as qualified as Xuedong Huang to talk about AI-first workplaces. For real. Now the CTO of Zoom, Xuedong (Known as XD) previously spent 30+ years bringing productivity software working at Microsoft. So, what do we need to know? Xuedong's gonna share all! Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan and Xuedong questions on AI in the workplaceUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Changes in the Workplace Due to AI2. Adapting an AI-First Workplace3.Integration of GUI and Conversational User InterfaceTimestamps:00:00 Technology, AI transform modern workplace productivity.06:42 Effective transition to future work with AI.08:33 Daily assistant enhances productivity and information consumption.11:18 AI changes productivity in meetings, reading, writing.16:58 Appreciate expert insights on strategic AI application.17:35 Charting future for widely-used technology products.20:42 Unlearn habits; embrace AI in the workplace.25:46 Hope and advice for AI-driven workplaces.Keywords:Zoom, AI Companion, Generative AI, AI First Workplace, AI Tools, Large Language Models, Productivity, Technology, Microsoft, Google, Google Docs, Microsoft Word, Internet, Workplace, Mobile Phones, Web, Cloud, Action Items, Meetings, email, Typewriter, Desktop Computing, Collaboration, Task Tracking, Anthropic, Google Gemini, GBT 4, GUI, AUI, Web Search Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/