Podcasts about Mig

Ron "Toes" Cooper grew up silent, insecure, and certain he'd never amount to much. Then four men believed in him — and everything changed. Toes went on to fly the F-4 Phantom in over 300 combat missions in Vietnam, dodge a MiG-21 missile by a split second, participate in the rescue of a downed pilot who survived 23 days alone in hostile territory, and command a squadron. In this episode, Toes brings us into the cockpit and into the chaos of combat — and then draws a straight line from those experiences to the leadership lessons that every team, every organization, and every person who has ever doubted themselves desperately needs to hear.Support this podcast at — https://redcircle.com/the-fighter-pilot-podcast/donations

Siempre que se habla de la aviación de la Guerra de Vietnam se recuerda a los cazas: el Phantom, el Mig-21, en ocasiones al Crusader… en otras incluso recuerdan a los bombarderos, como el B.52. Pero hay muchos otros aviones totalmente desconocidos de los que nunca se acuerda nadie. Menos Héctor y Jose. P.D.: Si la intro y la despedida os son familiares, que no os sorprenda. En un ejercicio de nostalgia podcasteril he hablado con Javier Lago para pedirle permiso y utilizar la introducción que hizo para el que, si no recuerdo mal, fue el primer podcast español sobre aviación: Remove Before Flight RBF podcast

Vallningar, hjärndimma och att inte riktigt känna igen sig själv. Lyssnarna delar med sig av sina erfarenheter av att själv vara i, eller nära någon som är i klimakteriet. Lyssna på alla avsnitt i Sveriges Radios app. Klimakteriet är sällan något som bara händer en person – det påverkar ofta hela livet runt omkring. I dagens program handlar det om din relation till klimakteriet, både om du själv är i det och om du står bredvid: som partner, vän, kollega, vuxet barn eller nära anhörig.Ibland märks det mest i det lilla: trötthet som aldrig släpper, kortare tålamod, en kropp som känns annorlunda, en natt med stökig sömn. Och för den som är nära kan det väcka frågor, eller kanske en vilja att förstå men inte riktigt veta hur man ska göra. Sex av tio kvinnor i Sverige i åldrarna 40–60 år rapporterade klimakteriesymtom under det senaste året. Bland de kvinnor som sökt vård upplevde mindre än hälften av kvinnor i åldrarna 40–44 år att de fått adekvat hjälp, berättar Folkhälsomyndigheten i en ny undersökning.Hur har klimakteriet ditt liv? Dela med dig av din historia i Karlavagnen.Klimakterieterfarenheter i Karlavagnen med Sarit MonastyrskiRing oss, mejla på karlavagnen@sverigesradio.se eller skriv till oss på Facebook och Instagram. Slussen öppnar kl 21:00 och programmet börjar 21.40

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop interviews Joshua Pearce, the John Thompson Chair in Innovation at the Department of Electrical and Computer Engineering and Ivey Business School at Western University, about the revolution in open source hardware for scientific research. They discuss how three-dimensional printing, Arduino controllers, and open source designs are dramatically reducing research costs—often by 85-95%—while democratizing access to lab equipment worldwide. Pearce shares stories from his 2013 book "Open Source Lab" and explains how the movement has exploded since then, covering everything from filter wheel changers and ball mills to metal three-dimensional printers and battery research equipment. The conversation explores recycle bots that turn plastic waste into filament, the role of AI in accelerating hardware development, and how open source licensing creates a global knowledge management system where improvements are shared across the scientific community. For those interested in learning more, Pearce recommends checking out the journal HardwareX, repositories like Thingiverse and My Mini Factory, and appropedia.org for open source scientific tools and appropriate technology designs.Timestamps00:00 Welcome and introduction to Joshua Pearce, discussing his work on open source lab equipment and the evolution since publishing his book in 201305:00 Early development of open source hardware including the breakthrough filter wheel changer project built by a high school student that saved thousands of dollars10:00 Discussion of how Arduino and RepRap three-d printers enabled the democratization of scientific tools, making complex equipment accessible to anyone15:00 Economic impact showing average tool savings of 85 percent, with Arduino and three-d printing combinations reaching mid-90s percent cost reduction20:00 Case study of PhD student Mariam building complete battery research tool chain from scratch using open source designs and three-d printed components25:00 Recycle bots enabling transformation of waste plastic into three-d printer filament for pennies, revolutionizing material costs and sustainability30:00 Collaboration between universities and open source companies creating fluid handlers and acquisition systems, accelerating research capabilities globally35:00 Large language models assisting code translation and research planning, though hallucinations require careful verification and domain expertise40:00 Importance of fundamental knowledge when using AI tools, comparing vibe coding acceleration with necessity for understanding underlying principles45:00 Testing standards and calibration methods for open source equipment, balancing precision requirements against cost-effectiveness for specific applications50:00 Metal and ceramic three-d printing developments including MIG welding techniques and sintering processes for creating functional parts55:00 Knowledge management through open source licenses, repositories like Thingiverse and Apropedia enabling global collaboration and continuous improvementKey Insights1. Open source hardware has evolved dramatically since Joshua Pearce wrote his book in 2012-2013, to the point where he can no longer keep up with all the developments in the field. What started as a collection where every single example could fit in one book has exploded into an entire ecosystem with dedicated journals and thousands of researchers contributing. The vision was that scientific papers would eventually include hyperlinks to equipment designs that anyone could download and replicate, and that future is largely here today. There are now so many open source hardware articles being published that no single person can read them all, which represents a massive success for the movement.2. The fundamental breakthrough enabling open source scientific hardware came from combining several key technologies, particularly the RepRap three-d printer project and Arduino microcontrollers. Pearce's introduction to the field came when he needed a sixty-five dollar plastic part for a solar laptop project and discovered Adrian's open-sourced rapid prototyper that could make its own parts. This led to building equipment like a filter wheel changer for testing solar panels with a high school student in about a week, replacing a device that would have cost two thousand five hundred dollars with five months lead time. The democratization of tools like three-d printing and Arduino, combined with extensive code libraries and shared designs, means that even high school students can now create sophisticated scientific equipment.3. Open source scientific hardware delivers massive economic benefits, with the average tool saving scientists around eighty-five percent compared to commercial equipment, and savings reaching the mid-nineties when using Arduino and three-d printing. The economics are so compelling that the tax paid on a normal scientific tool can cover the cost of an open source alternative. A thousand dollar three-d printer can manufacture scientific tools worth more than a thousand dollars in a single Saturday. This dramatic cost reduction makes sophisticated research accessible to laboratories around the world regardless of their funding levels, fundamentally democratizing scientific capability.4. The knowledge management approach enabled by open source licenses creates a powerful collaborative improvement cycle where thousands of people worldwide contribute to evolving designs. When researchers publish equipment designs with strong reciprocal licenses, anyone can use, modify, or even sell the designs, but improvements must be shared back with the community. This creates a dispersed international engineering effort where equipment continuously improves through contributions from researchers across different institutions and countries. The RepRap three-d printer exemplifies this process, starting as barely functional prototypes but evolving through community contributions to surpass commercial alternatives in speed, resolution, and material capabilities.5. The integration of large language models and AI tools has significantly accelerated open source hardware development, though with important caveats about their limitations. LLMs excel at translating code between languages, suggesting experimental approaches, and helping researchers navigate unfamiliar fields by quickly synthesizing information from scientific literature. However, they suffer from hallucination problems and cannot be trusted for writing scientific articles or conducting complete literature reviews without verification. The key to effective use is having enough foundational knowledge to ask the right questions and verify outputs, using AI as a powerful acceleration tool rather than a replacement for expertise.6. Material science capabilities in open source hardware have expanded far beyond plastic three-d printing to include metals, ceramics, semiconductors, and composites through innovative adaptations of basic equipment. Pearce's lab has developed methods for metal three-d printing using modified MIG welding for as little as twelve hundred dollars, created slot-die coating systems for seventeen nanometer semiconductor layers using converted three-d printers, and developed techniques for ceramic printing through various material mixing approaches. The recycle bot technology enables converting waste plastic into high-quality filament for twenty-five cents instead of twenty-five dollars per roll, dramatically reducing material costs while enabling circular manufacturing practices.7. The infrastructure for sharing and discovering open source hardware designs has matured into a robust ecosystem spanning academic journals, commercial repositories, and specialized communities. Hardware X and the Journal of Open Hardware publish peer-reviewed designs alongside traditional scientific journals increasingly incorporating open hardware sections. Repositories like Thingiverse recently returned to hardcore open source principles after ownership changes and contains millions of designs, while Appropedia serves as a wiki for appropriate technology with thousands of open source designs. The GOSH community hosts annual conferences bringing together university researchers, companies, and independent hardware hackers, while field-specific communities have formed around technologies like the OpenFlexure microscope, creating networks where knowledge accumulates and never gets lost.

Den här veckan möter vi Clara Vennman, folkhögskolelärare och aktiv i Equmeniakyrkan i Göteborg. Hon tar sin utgångspunkt i hoppet. Lyssna på alla avsnitt i Sveriges Radios app. Ur andakten:För det är så - vi människor behöver något att tro och hoppas på. Om det är de goda nyheterna som tar vår uppmärksamhet - så är det också det som vi sedan vill dela med andra.Evangelium kommer från det grekiska ordet “evangelion” och betyder ungefär “gott budskap” eller “glädjebudskap”. Det är grunden för hela kyrkan och den kristna församlingen - de goda nyheterna som ska spridas världen över. Och att vi ska få höra det om och om igen. Berättelsen om hur Gud genom historien, och än idag, visar sin kärlek till hela mänskligheten. Att det aldrig är ute med oss, vare sig Dig eller med Mig. Det är berättelser som ger både hopp, mening och sammanhang.Musik:Kom Du Källa med Erik Tilling och Michael Jeff Johnson, komponerad av Shane Bernard, Paul Biktor Börjesson och Robert RobinsonProducent:Susanna Némethliv@sverigesradio.se

Agradece a este podcast tantas horas de entretenimiento y disfruta de episodios exclusivos como éste. ¡Apóyale en iVoox! El legado del famoso delta de Dassault fue un avión totalmente diferente, que rompió con la configuración alar que hizo famosos a los cazas franceses, y que arregló todo aquello que fallaba en el Mirage III/5, como la maniobrabilidad, el alcance, o la visibilidad. Pero el Mirage F.1 no fue el mejor en nada en medio de aviones tan capaces como los F-16, MiG-23 o Viggen. Pero precisamente por no ser mejor en nada, fue el que pudo hacerlo todo: proteger los cielos, atacar a buques y a tanques, o a instalaciones en profundidad, espiar los movimientos enemigos, y operar en aeródromos que solo lo son de nombre. Su polivalencia le hizo ganarse de nuevo un hueco, no solo en la Armée de l'Air, sino en países con condiciones duras... y en España, que compartió el cielo con los Mirage III, los Phantom y los F-18. ◼️ Edición Limitada Versus Vol.1 👉 https://go.ivoox.com/sq/3153351 ◼️ 🆕 ENLACE A TODOS LOS CB FANS 💥 https://t.me/+1uHtwikQTZ85ZWRk 📧¿Queréis contarnos algo? puedes escribirnos a casus.belli.pod@gmail.com Casus Belli Podcast pertenece a 🏭 Factoría Casus Belli. Casus Belli Podcast forma parte de 📀 Ivoox Originals. 📚 Zeppelin Books zeppelinbooks.com es un sello editorial de la 🏭 Factoría Casus Belli. Estamos en: 👉 https://podcastcasusbelli.com 👉 X/Twitter https://twitter.com/CasusBelliPod 👉 Facebook https://www.facebook.com/CasusBelliPodcast 👉 Instagram estamos https://www.instagram.com/casusbellipodcast 👉 Telegram Canal https://t.me/casusbellipodcast 👉 Telegram Grupo de Chat https://t.me/casusbellipod 📺 YouTube https://bit.ly/casusbelliyoutube 👉 TikTok https://www.tiktok.com/@casusbelli10 👨💻Nuestro chat del canal es https://t.me/casusbellipod ⚛️ El logotipo de Casus Belli Podcasdt y el resto de la Factoría Casus Belli están diseñados por Publicidad Fabián publicidadfabian@yahoo.es 🎵 La música incluida en el programa es Ready for the war de Marc Corominas Pujadó bajo licencia CC. https://creativecommons.org/licenses/by-nd/3.0/ El resto de música es bajo licencia privada de Epidemic Music, Jamendo Music o SGAE SGAE RRDD/4/1074/1012 de Ivoox. ¿Quieres anunciarte en este podcast, patrocinar un episodio o una serie? Hazlo a través de 👉 https://www.advoices.com/casus-belli-podcast-historia Si te ha gustado, y crees que nos lo merecemos, nos sirve mucho que nos des un like, ya que nos da mucha visibilidad. Muchas gracias por escucharnos, y hasta la próxima. ¿Quieres anunciarte en este podcast? Hazlo con advoices.com/podcast/ivoox/391278 Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Den här veckan möter vi Clara Vennman, folkhögskolelärare och aktiv i Equmeniakyrkan i Göteborg. Hon tar sin utgångspunkt i hoppet. Lyssna på alla avsnitt i Sveriges Radios app. Ur andakten:Bibeln berättar om att Gud ser på oss människor, på Dig och Mig, med samma varma blick. Redan i Första Mosebok så berättas det om hur Gud skapar hela världen och allt levande. Han skapar grönska, fröbärande örter och träd - och ser att det är gott. Han skapar ljus och mörker och stjärnorna att lysa över himlavalvet. Och Gud skapade alla dom levande varelserna: fyllde vattnet med liv och fåglar som skulle flyga över jorden. Och han såg att det var gott. Och till sist skapade han också människan, till sin egen avbild och välsignade dem.Sedan beskrivs det hur Gud såg allt han gjort, och se, det var mycket gott. Redan i skapelsen placerade Gud sin varma blick på sin mänsklighet.Text:Psaltaren 139:7-12Musik:Kom Du Källa med Erik Tilling och Michael Jeff Johnson, komponerad av Shane Bernard, Paul Biktor Börjesson och Robert RobinsonProducent:Susanna Némethliv@sverigesradio.se

In this engaging interview, Anthony Marin shares his inspiring journey from Brooklyn to becoming a successful real estate investor and property management entrepreneur. Discover his insights on building relationships, serving tenants with empathy, overcoming adversity, and scaling in the real estate market.   Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind:  Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership:  Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true 'white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright:  Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a "mini-mastermind" with Mike and his private clients on an upcoming "Retreat", either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas "Big H Ranch"? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform!  Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

Præludium: Leopold Mozart: Scherzo Fra det N.T.: Jeremias 23, 1-6 Salme: 141, vers 1-4 "Mig lyster nu at træde" Fra det N.T.: Matthæusevangeliet 3, 13-17 Korvers: Franz Schubert: Hellig, hellig, hellig (tekst: Johan Philipp Neumann/Poul Pedersen) Salme: 141, vers 5 Postludium: Gottfried August Homilius: Trio i G-dur

Rob “Z-Man” Zettel shares his story from inside one of the Air Force's most secret Cold War programs, Project Constant Peg.In this episode, Host Rick Crandall talks with Z-Man, a retired U.S. Air Force fighter pilot and former member of the legendary 4477th Test and Evaluation Squadron, the “Red Eagles,” about what it was like to fly real Soviet MiG fighters in the Nevada desert. From the F-4 Phantom and F-5 aggressors to the MiG-21 and MiG-23 at Tonopah Test Range, Zettel offers a firsthand look inside the classified program designed to train American pilots against the real thing. This one is going to be cool!

Om den där gången lyssnarna överträffade sig själva mot alla odds. Hör lyssnarnas berättelser här! Lyssna på alla avsnitt i Sveriges Radios app. Hanna har sprungit Stockholms marathon! I dagens program handlar det om när du gjorde något du inte trodde att du kunde, trotsade en rädsla eller lyckades mot alla odds. Ibland händer det där som förändrar självbilden, man gör något man länge trott att man inte skulle våga eller kunna. Det kan vara att trotsa en rädsla, ta ett steg som känts omöjligt, eller lyckas med något mot alla odds och plötsligt stå där och tänka: ”Det där gjorde jag.”Vad var ditt ögonblick? Dela med dig av din historia i Karlavagnen.Om att göra något en trodde inte var möjligt med Hanna Sihlman i KarlavagnenRing eller mejla oss, på karlavagnen@sverigesradio.se eller skriv till oss på Facebook och Instagram. Telefonslussen öppnar kl. 21.Programmet startar kl. 21:40.

Susanne släktforskar i sin biologiska pappas bakgrund. Men när hon ber sin halvbror DNA-testa sig ställs att på ända. Vem är egentligen barn till vem? Lyssna på alla avsnitt i Sveriges Radios app. Har du avslöjat en familjehemlighet som förändrat ditt liv? Hör då av dig till programmet och Gunilla Nordlund så kan din berättelse bli ett nyttavsnitt av serien. Maila till familjehemligheten@sverigesradio.seProducent för serien är Ola Hemström.

Och varför är en låt nästan alltid mellan tre och fem minuter? Låtskrivaren och författaren Annika Norlin svarar på lyssnarnas frågor. Lyssna på alla avsnitt i Sveriges Radios app. Sven vet massor om hur han ska hantera sitt liv och sin hälsa: sova sju timmar varje natt, motionera 30 minuter om dagen, höja pulsen tre gånger i veckan och vara socialt aktiv. Han har en lista över saker som ska göras för att hans bostad ska bli trivsam och inbjudande. Ändå sitter han timtals vid datorn och läser och gör listor på allt som ska göras. Varför är det så, frågar han.Joakim frågar: Varför är en låt nästan alltid mellan tre och fem minuter?Hur kommer det sig att män generellt är mer konservativa politiskt och mindre toleranta mot minoriteter som till exempel invandrare och homosexuella, undrar Mari. Hon har själv två söner och frågar: Vad kan jag som mamma göra för att de ska bli generösa, humana medborgare, med ett öppet sinne för olikheter? Hör Annika Norlin svara på lyssnarnas frågor. Har du själv en fråga som du vill rikta till författarna så mejla till: allvarligttalat@sverigesradio.seProducent: Karin Arbsjö

Rob "Z-Man" Zettel is a retired U.S. Air Force Lieutenant Colonel, commercial airline captain, and author of American MiG Pilot who served as a top-secret Red Eagles instructor pilot flying Soviet MiG-21 and MiG-23 fighter jets during the Cold War program Constant Peg.   American MiG Pilot: Inside the Top Secret USAF “Red Eagles” MiG Squadron: https://amzn.to/4fLi2DA Air Force Officer Qualifying Test (AFOQT) Prep with AFOQT Wingman https://afoqtwingman.com/Code: AFTERBURN for 10% off

Tusentals studenter ska snart ut i arbetslivet, men ibland blir det inte riktigt som man tänkt sig. Karlavagnen om när man var klantade sig på jobbet. Lyssna på alla avsnitt i Sveriges Radios app. Studenten och examen stundar och en drös med ungdomar är på väg ut i arbetslivet. Men handen på hjärtat, ibland går det inte riktigt som man tänkt sig. Det skiter sig helt enkelt. Lyssnarna delar med sig av pinsamma ögonblick på jobbet. Om missar på jobbet i Karlavagnen med Gerhard StenlundRing oss, mejla på karlavagnen@sverigesradio.se eller skriv till oss på Facebook och Instagram. Slussen öppnar klockan 21:00 och programmet börjar klockan 22:12.

Agradece a este podcast tantas horas de entretenimiento y disfruta de episodios exclusivos como éste. ¡Apóyale en iVoox! Acceso anticipado para Fans - ** VIDEO EN NUESTRO CANAL DE YOUTUBE **** https://youtube.com/live/xeydaV2D848 +++++ Hazte con nuestras camisetas en https://www.bhmshop.app +++ En este programa especial de Bellumartis, analizamos el punto de inflexión de la Segunda Guerra Mundial: La Batalla de Moscú. Junto al historiador y autor Cristóbal Vergara Durán, autor de "LOS AVIONES DE CAZA SOVIÉTICOS 1936-1941" ** https://amzn.to/4vgMgnn ** exploramos la defensa aérea del Kremlin y cómo la tecnología aeronáutica soviética, a menudo subestimada, fue capaz de frenar a la invicta Luftwaffe. A través del material exclusivo del libro de Cristóbal, realizamos un recorrido técnico y operativo que va desde los duelos en la frontera durante la Operación Barbarroja hasta la épica contraofensiva de invierno que salvó la capital soviética. Estructura del programa: El Legado Técnico: Análisis de los modelos I-153, I-16, y la llegada de la nueva generación: MiG-3, Yak-1, LaGG-3 y el imponente Pe-3. El Escudo de Moscú: La campaña de bombardeos sobre la capital y la respuesta de las VVS. Grandes Cercos: El impacto de las batallas de Kiev y el asedio de Leningrado en la estrategia aérea. Operación Tifón: El asalto final alemán y la resistencia en los cielos de los Urales. Arsenal de la Democracia: El papel fundamental de la ayuda aliada con los Hurricane y P-40. Contraataque bajo el Hielo: La contraofensiva de invierno y las conclusiones de una campaña que cambió el mundo. SUSCRÍBETE a @BELLUMARTISHISTORIAMILITAR y @BELLUMARTISACTUALIDADMILITAR para no perderte ningún programa y únete a nuestra comunidad de apasionados por la historia militar, la geopolítica y los conflictos del mundo. Apóyanos para seguir creando contenido riguroso e independiente: Patreon: https://www.patreon.com/bellumartis PayPal: https://www.paypal.me/bellumartis Bizum: 656 778 825 Síguenos también en redes: Instagram: https://www.instagram.com/bellumartis Twitter / X: https://twitter.com/Bellumartis Bellumartis Historia Militar — Porque entender el pasado es prepararse para el futuro. #BatallaDeMoscu #HistoriaMilitar #Bellumartis #WW2 #CazasSovieticos #CristobalVergara #FrenteDelEste #AviationHistory #SegundaGuerraMundial #EstrategiaEscucha este episodio completo y accede a todo el contenido exclusivo de BELLUMARTIS PODCAST. Descubre antes que nadie los nuevos episodios, y participa en la comunidad exclusiva de oyentes en https://go.ivoox.com/sq/618669

Jim “JB” Bell shares his story from inside one of the Air Force's most secret Cold War programs, Project Constant Peg.In this episode, Host Rick Crandall talks with Jim, a retired crew chief of the legendary 4477th Test and Evaluation Squadron, about what it took to keep MiG fighters flying in the Nevada desert. From maintaining MiG-17s, MiG-21s, and MiG-23s at Tonopah Test Range to flying on unmarked C-5s into China and bringing home F-7 fighters, Bell offers a rare perspective on one of the most classified adversary air programs in U.S. Air Force history. This one is going to be cool!

We're Listen Like Fans podcast is back with Season 2, whoohoooo.... And in this week's episode, we're delighted to have on the Listen Like Fans podcast the extremely versatile and talented 'MiG' Ayesa - or to give him his full name, Miguel Alfonso Ramon Legarda Ayesa. As many INXS fans will remember, MiG was a contestant on RockStar INXS. Mig was one of the final three contestants and became a frontrunner with versions of "Live and Let Die" and "Baby, I Love Your Way".  MiG joins Bee from a cruise ship in a wide-ranging career interview to discuss all things performing on TV, studio and stage - including singing in multiple languages such as Japanese! In the twenty years since RockStar INXS ended, Mig has enjoyed a successful music career, releasing solo albums, working in theatre and appearing in television and film.  On the podcast today, MiG talks about his break into theatre in London's West End and meeting the surviving members of rock band Queen for his lead stint in We Will Rock You. All this would change, however, when Mig decided to try his luck auditioning for a new reality TV programme... Auditioning at the Shepherd's Bush Empire in London to the INXS classic 'I Send a Message', a certain Mr Pengilly would be in the audience watching. This led to a second audition and then making the final 50 cut to perform in Los Angeles.  MiG recounts the laborious process of filming for each round of the RockStar INXS audition and eventually making it into the last 15. During his time with RockStar INXS, 'Baby, I Love Your Way', the Peter Frampton classic, became one of the standout performances of the entire series. MiG takes us behind the scenes and explains how the songs were chosen and how he came up with the arrangement to make the song his own.  In something of a fortuitous twist of fate, this would lead to Peter Frampton playing acoustic guitar on MiG's debut album. Talking about his debut solo album, MiG gives the inside on how Mötley Crüe's Tommy Lee was responsible for MiG's debut album being shelved by the record label for two years!  Finally, MiG talks reuniting with the original RockStar INXS house band and many of the contestants for the upcoming anniversary shows at the Avalon in Hollywood. With more than 25 years in the industry, MiG has had a varied and interesting career, and the signs are that there are plenty more twists and turns to come. We hope you enjoy listening to the very entertaining MiG and feel inspired to check out his back catalogue. Links below.   Until next time, keep listening like fans! Bee!   If you're a patron of Listen Like Fans, you can watch this interview here:  https://www.patreon.com/posts/early-access-mig-158129922?utm_medium=clipboard_copy&utm_source=copyLink&utm_campaign=postshare_creator&utm_content=join_link https://rockstarreunionlive.com/ https://open.spotify.com/album/0wzSGWKgpVelYpjPI5XTVQ?si=uHXWtXXfToGoKIsF6G6aow

In the depths of the Castle Eschatonica, the true beckonings called to the travelers of the Dragon Path. Led across the ether under divine shadow and holy light, to things that aren't, but which might yet be: New more peaceful lives. Freedom from obligation and duty. Different, more adventurous histories. A key to a door which itself beckons. The power to protect those they care for. Power for power's sake alone. With these behind them, the two groups re-emerge into the halls of the Castle. In the western wing, three figures push forward into the passageways of this transcendent fortress—Uncle Nicky, criminal turned chef; the terrapine Jonathan, inventor and—now—airship captain; and Antistrophe Landrace, the Ruinbringer, though he may not know it yet.  Meanwhile, to the east, an octet walks Eschatonica's twisting paths: Famed adventurer, and Jonathan's sister, Maebela; Veile Lyndelle, destined devotee of the Ennead; Elena Millefiori, Tesserae chanter and eager traveler; the youthful and curious Waylon of Spillaway Peaks; Renegade Hexcloak Caiomhe Wake; and finally, Brontë Adelvys, dissipated sixth scion of the First Line, along with his attendants, Efta and Zolfta Above them, watching with all nine eyes, is Gnova, once the God of Distant Color and Light, now the steward of this Castle. But they are not the only celestial being interested in Eschatonica. They saw Lucena's sunlight streamed across the ether towards their home. They watched as Caliginia's long shadow fell, finally, even here. Indeed, they dread how these gods now shake the diorama-like stability of Eschatonica, and how in doing so, they unknowingly have sent up a flare… Because she is coming, now. Indeed. She is almost here. This Week on Perpetua: Escape the Rumbling Castle! 01 Perpetua Guide [In Progress v.06] NPCs & Monsters [PNMS] Thanks to TheUnforgivenIII for pushing me to include a little more info in the NPCs & Monsters section! Still not giving it all away, because my goal isn't to take away all the mystery! But you should check TU3's strategy guide (in progress) for more combat focused tips! Windborne Hawk Traits: Agile, Lightweight, Droning Type: Hunter Construct Level: 10 Rank: Soldier Stats: DEX 10, INS 8, MIG 6, WLP 8  Attacks: Flechette Burst Special Abilities: Occult Dampener, Annoying Buzz, Flying Elemental Affinities: IMM: Poison | RES: Wind, Dark, Earth | VUL: Bolt, Ice, Light In-Game Description: A beautiful bird automaton that floats through the power of a dark wind. Despite being level 10 soldiers, these are one of the most dangerous enemies in the Castle Eschatonica. They are custom made to crush your casters (which according to DoomTreeAnne's lore document really lines up with their anti-Oracle purpose in Armidirge). Their Flechette Burst can tear through your party (especially characters without martial armor!!) and their Occult Dampener turn them into spell-devouring TANKS.   Starter Tip: Take. These. Down. Quick. Once their Dampener is up, they're that much harder to deal with. Windborne Turret Traits: Automatic, Threat-Finding, Defensive, Deployed Type: Hunter Construct Level: 10 Rank: Soldier Stats: DEX 8, INS 10, MIG 8, WLP 6  Attacks: Repeating Fire Special Abilities: None Elemental Affinities: IMM: Poison | RES: Wind, Dark, Earth | VUL: Bolt, Light In-Game Description: A hovering, bronze-clad weapon that scans for (and eliminates) targets Extremely straightforward enemies. They float in place (but AREN'T Flying enemies) and take a really strong shot at you every other turn (and it doesn't seem like they do much in the way of supporting the rest of their side).  Exploit that to keep their total attack Starter Tip: Focus them down, one at a time. Windborne Flower Traits: Automatic, Defensive, Deployed Type: Support Construct Level: 10 Rank: Soldier Stats: DEX 8, INS 8, MIG 8, WLP 8 Attacks: Shadow Cast Special Abilities: Barrier of Wind, Flying Elemental Affinities: IMM: Poison | RES: Wind, Dark, Earth | VUL: Bolt, Fire, Light In-Game Description: Like a bronze flower, this device unfurls its petals and emits a shielding over its allies. These are the de facto "clerics" of these Windborne automata. Their Barrier of Wind is super annoying (though it should be recognizable if you're doing a support Elene build!).  Starter Tip: While they don't do a lot of damage, their Shadow Cast ability can leave your party dazed, so be careful! Eaja, Windborne Hawkmaster Traits: Fierce, Quick, Determined, Principled Type: Sentinel Humanoid Rank: Champion (3) Stats: DEX ??, INS ??, MIG ??, WLP ??  Attacks: Unknown Special Abilities: Unknown Elemental Affinities: Unknown In-Game Description: A scout from the Windborne Church, one of the two major factions of Armidirge. Thankfully, you don't need to fight Eaja along with her automatons when you first bump into her, though if you're quick you can tackle her as an optional boss fight (which is really hard). Starter Tip: Leave her for later! Trust me. Hosted by Austin Walker (austinwalker.bsky.social) Featuring Ali Acampora (ali-online.bsky.social), Art Martinez-Tebbel (amtebbel.bsky.social), Jack de Quidt (notquitereal.bsky.social),  Janine Hawkins (@bleatingheart), Sylvi Bullet (@sylvibullet), Keith J Carberry (@keithjcarberry) and Andrew Lee Swan (swandre3000.bsky.social) Produced by Ali Acampora Music by Jack de Quidt (available on bandcamp) Cover Art by Ben McEntee (https://linktr.ee/benmce.art) With thanks to Amelia Renee, Arthur B., Aster Maragos, Bill Kaszubski, Cassie Jones, Clark, DB, Daniel Laloggia, Diana Crowley, Edwin Adelsberger, Emrys, Greg Cobb, Ian O'Dea, Ian Urbina, Irina A., Jack Shirai, Jake Strang, Katie Diekhaus, Ken George, Konisforce, Kristina Harris Esq, L Tantivy, Lawson Coleman, Mark Conner, Mike & Ruby, Muna A, Nat Knight, Olive Perry, Quinn Pollock, Robert Lasica, Shawn Drape, Shawn Hall, Summer Rose, TeganEden, Thomas Whitney, Voi, chocoube, deepFlaw, fen, & weakmint This episode was made with support from listeners like you! To support us, you can go to friendsatthetable.cash.

Habba, Danny och Tim har sprungit ett jävla blufflopp och Björn har slarvat bort en ovärderlig kulturklenod. Dessutom har ännu en MiG-bebis anlänt till världen!

Today on the radio show. 1 - Smoko chat. 4 - Working from the Cricket. 7 - Coin of destiny. $750,000 tractor flip. 11 - Scott and Mig. Hutchwilko boat show. 16 - Crazy, but it’s true. 19 - Benny Boy cooked mothers day. 23 - Right event, wrong date. 27 - The fat plane. 28 - Late mail. 32 - last drinks.

Helgen är framför oss! Men vad har lyssnarna framför sig? Lyssna på alla avsnitt i Sveriges Radios app. Ett nyfiket och underhållande aktualitetsprogram med lyssnaren i fokus.Kerstin har en vävstol och en snart klar matta framför sig, Magnus har en ”efter-spa-öl” i handen och Per ska snart kolla på en fotbollsmatch! Dessutom tävlar Paula och Ninni i Rasmus tävling ”Gissa grej framför mig”.I extramaterialet pratar vi om vad som har hållit Rasmus vaken om nätterna och så säger vi hejdå till vår praktikant Saga.

Valborg är förbi och våren är här! För många framkallar det nya känslor ljus, energi, kanske hopp. Lyssna på alla avsnitt i Sveriges Radios app. Vi pratar om musiken som väcker just dina vårkänslor, oavsett om dom är ljusa, vemodiga eller någonstans mitt emellan.Vilken musik får dig att känna att vintern äntligen släpper taget? Den där låten som ger vårpirr i kroppen och ger dig känslan av att något nytt är på gång.Eller väcker våren helt andra känslor hos dig än bara pirr och pepp. Säg det med en sång - ikväll vill vi höra om dina vårkänslor – hur de än låter.Vårens spellista, med Magnus Broni i KarlavagnenRing oss, mejla på karlavagnen@sverigesradio.se eller skriv till oss på Facebook eller Instagram. Slussen öppnar kl 21:00 och programmet börjar ca kl 21:40

Undanfarna viku hefur staðið yfir vitundarvakningin ÉG LOFA á vegum Barnaheilla. Markmiðið var að vekja athygli á umfangi kynferðisofbeldis gegn börnum með því að miðla upplýsingum og fræðslu. Kolbrún Hrund Sigurgeirsdóttir verkefnisstýra ofbeldis- og kynheilbrigðismála hjá Barnaheillum kom í þáttinn í dag og sagði okkur aeðins frá þessu átaki og einnig frá ungmennaþingum sem haldin voru á sex stöðum á landinu þar sem rætt var um kynferðisofbeldi í nánum samböndum ungmenna og það sem þar kom fram á þessum þingum er vægast sagt sláandi. Hrafnhildur Reykjalín er starfandi heilsuráðgjafi á Akureyri, hún er kennari í markþjálfun með diplómu í jákvæðri sálfræði auk fjölbreyttrar menntunar í andlegri og líkamlegri heilsu og önnur eigenda Sjálfsræktar heilsumiðstöðvar. Í jákvæðri sálfræði og markþjálfun er unnið markvisst með gildi sem grunn að vellíðan og stefnu í lífinu. Hrafnhildur sagði okkur betur frá þessu í þættinum í dag. Svo var komið að síðasta skiptinu í bili sem Valdimar Þór Svavarsson kemur til okkar til að ræða mannlegu samskiptin. Hann hefur verið með okkur alla fimmtudaga í vetur og í síðustu viku fór hann yfir það helsta sem hann hefur talað um og í dag fór hann yfir nokkur góð ráð til að brjóta upp mynstur og venjur sem eru ekki að þjóna okkur. Tónlist í þættinum í dag: Létt / Ríó Tríó (Gunnar Þórðarson, texti Jónas Friðrik Guðnason Mig dreymir / Björgvin Halldórsson (Björgvin Halldórsson, texti Jónas Friðrik Guðnason) Kastað á glæ / Geirfuglarnir (Halldór Gylfason) Þér við hlið / Regína Ósk Óskarsdóttir (Magnús Þór Sigmundsson, texti Trausti Bjarnason) UMSJÓN: GUÐRÚN GUNNARSDÓTTIR OG GUNNAR HANSSON

V novej epizóde relácie Za hranicou bola témou vzdušná obrana Slovenska. Na začiatku sme sa s hosťom venovali komentáru od ďalšieho z našich hostí - leteckého inžiniera Vladimíra Koláčeka. Hovorili sme o MiG-29 a prečo oficiálne informácie o dostreloch zbraní nie sú vždy presné. Neskôr sme sa venovali novej leteckej posile pre Slovensko, a to stíhačkám F-16 a izraelskému obrannému systému Barak MX. Pozvanie do relácie prijal bezpečnostný analytik Vladimír Bednár.

Get the full episode here: https://www.10percenttrue.com/pricing-plans/listIn Episode 3, Benji Prefontaine takes you into the most demanding phase of his combat experience—flying the Dassault-Breguet Super Étendard over Afghanistan in a crowded, chaotic coalition battlespace.With limited sensors, minimal weapons, and no datalink, every mission becomes a test of situational awareness and judgment. He describes near-misses in mid-air, fuel emergencies, comms failures, and the constant risk of fratricide—all while supporting troops in contact on the ground.The central theme is stark: the biggest danger isn't always the enemy—it's the environment, the complexity, and your own decisions. Benji explains why the urge to drop a weapon can be the most dangerous instinct a pilot has—and why sometimes the right call is to hold fire.This episode is a raw, honest look at the reality of close air support—and the responsibility carried by the person in the cockpit.⸻0:00 intro teaser - CAS story2:40 Welcome back (Again!) Benji3:30 recap of Super E capabilities as deployment to Afghanistan looms6:28 Spinning up and deploying 9:02 commencing ops in a relatively quiet 200611:04 2007 tougher (expanded ops, integration of new Rafale capabilities)14:30 “joint” Navy buddy mission with Rafale on 27/03/07 (including 5:59:59 flameout)19:01 admin can kill you - fuel problems and deconfliction 22:48 2008 Carrier stood down for refit/repair so Super E is ground based at Kandahar 26:55 reviewing the learning points emerging from the initial engagement (including Damocles limitations and intro story)34:36 integration into ATO? 37:25 personal growth?42:24 USB exchange pilot contributions?44:48 full access? (and the perils of Super E cockpit for the well built gentleman)48:07 kneeboard capabilities 52:11 comms - satcom54:11 going back to F1, missing it, an adjustment?58:58 back to Kandahar in the F11:02:44 revisiting the psychological aspect in terms of Afghanistan (and Libya)1:06:41 Dollars!1:11:40 Libya - state of play/the vagaries of real world deployment and getting in on the action 1:23:50 the benefits of a tight knit community (moving a squadron whilst fighting a war and training new people) 1:29:58 the toll on family?1:32:42 threat levels in Libya1:37:22 XCAS and Intel?1:40:28 SCUD launcher mission1:44:00 tanker scarcity1:45:10 ATL21:46:12 QRA/policing/Chad (again)1:53:10 intercepts and “etiquette”1:55:30 flying with MiG-29SMTs2:00:17 drinking vodka with MiG-31 squadron cmdr 2:01:43 Foxhound intel?/diplomacy/history2:05:49 rounding out Air Force career and next chapter2:11:40 Merci Benji

Early bird discounts for the San Francisco World's Fair, the biggest AIE gathering of the year, end today - prices will go up by ~$500 tonight so do please lock in ASAP!From near-universal AI tool adoption inside Shopify to internal systems for ML experimentation, auto-research, customer simulation, and ultra-low-latency search, Mikhail Parakhin joins us for a deep dive into what it actually looks like when a 20-year-old, $200B software company goes all-in on AI. We cover why Shopify has become much more vocal about its internal stack, what changed after the December model-quality inflection, and why the real bottleneck in AI coding is no longer generation, but review, CI/CD, and deployment stability.We also go inside Tangle, Tangent, SimGym, which are three major AI initiatives that Shopify is doing to make experimentation reproducible, optimization automatic, customer behavior simulatable, and search and catalog intelligence faster and cheaper at scale. Along the way, Mikhail explains UCP, Liquid AI, and why token budgets are directionally right but often measured badly, why AI-written code can still increase bugs in production, what makes Shopify's customer simulation defensible, and what he learned from the Sydney era at Bing.We discuss:* Mikhail's path from running a major Microsoft business unit spanning Windows, Edge, Bing, and ads to becoming CTO of Shopify* Why Shopify is talking more publicly about AI now, and why staying at the frontier has become necessary for the company* Shopify's internal AI adoption curve, the December inflection, and why CLI-style tools are rising faster than traditional IDE-based tools* Why Jensen Huang is directionally right on token budgets, but raw token count is still the wrong way to evaluate engineering output* Why the real unlock is not more agents in parallel, but better critique loops, stronger models, and spending more on review than generation* Why AI coding can still lead to more bugs in production even if models write cleaner code on average than humans* Why Shopify built its own PR review flow, and why Mikhail thinks most off-the-shelf review tools miss the point* How PR volume, test failures, and deployment rollback are becoming the real bottlenecks in the agent era* Why Git, pull requests, and CI/CD may need a new metaphor once code is written at machine speed* What Tangle is, and how Shopify uses it to make ML and data workflows reproducible, collaborative, and production-ready from the start* Why Tangle is different from Airflow, and why content-addressed caching creates network effects across teams* What Tangent is, and how Shopify is using auto-research loops to optimize search, themes, prompt compression, storage, and more* Why Tangent is becoming a democratizing tool for PMs and domain experts, not just ML engineers* Why AutoML finally feels real in the LLM era, and where auto-research still falls short today* Why Tangle, Tangent, and SimGym become much more powerful when combined into one system* What SimGym is, why simulated customers only work if you have real historical behavior, and why Shopify's data gives it a moat* How SimGym evolved from comparing A/B variants to telling merchants what to change on a single live storefront to raise conversions* Why customer simulation is so expensive, from multimodal models to browser farms to serving and distillation costs* How Shopify models merchant and buyer trajectories, runs counterfactuals, and thinks about interventions like discounts, campaigns, and notifications* Why category-level behavior is so different across commerce, and why ideas like Chinese Restaurant Processes are showing up again in practice* Shopify's new UCP and catalog work, including runtime product search, bulk lookups, and identity linking* Why Shopify is using Liquid AI, and why Mikhail sees it as the first genuinely competitive non-transformer architecture he has used in practice* Where Liquid already works inside Shopify today, from low-latency query understanding to large-scale catalog and Sidekick Pulse workloads* Whether Liquid could become frontier-scale with enough compute, and why Shopify remains pragmatic and merit-based about model choice* Who Shopify is hiring right now across ML, data science, and distributed databases* The Sydney story at Bing, why its personality was not an accident, and what Mikhail learned from deliberately shaping AI character early onMikhail Parakhin* LinkedIn: https://www.linkedin.com/in/mikhail-parakhin/* X: https://x.com/MParakhinTimestamps00:00:00 Introduction: Mikhail Parakhin, Microsoft, and Shopify00:01:16 Why Shopify Is Talking More About AI00:02:29 Internal AI Adoption at Shopify and the December Inflection00:06:54 Token Budgets, Jensen Huang, and Why Usage Metrics Can Mislead00:10:55 Why Shopify Built Its Own AI PR Review System00:12:38 AI Coding, More Bugs, and the Real Deployment Bottleneck00:14:11 Why Git, PRs, and CI/CD May Need to Change for Agents00:18:24 Tangle: Shopify's Reproducible ML and Data Workflow Engine00:21:19 Why Tangle Is Different from Airflow00:26:14 Tangent: Auto Research for Optimization and Experimentation00:30:07 How Tangent Democratizes Experimentation Beyond ML Engineers00:33:06 The Limits of Auto Research00:36:36 Why Tangle, Tangent, and SimGym Compound Together00:37:20 SimGym: Simulating Customers with Shopify's Historical Data00:42:47 The Infra Behind SimGym00:46:00 Why SimGym Gets Better with Real Customer History00:47:30 Counterfactuals, HSTU, and Modeling Merchant Trajectories00:51:55 CRPs, Clustering, and Category-Level Customer Behavior00:53:30 UCP, Shopify Catalog, and Identity Linking00:55:07 Liquid AI: Why Shopify Uses Non-Transformer Models00:59:13 Real Shopify Use Cases for Liquid01:03:00 Can Liquid Scale into a Frontier Model?01:09:49 Hiring at Shopify: ML, Data Science, and Databases01:10:43 Sydney at Bing: Personality Shaping and AI Character01:13:32 Closing ThoughtsTranscript[00:00:00] swyx: Okay. We're here in the studio, a remote studio, with Mikhail Parakhin, CTO of Shopify. Welcome.[00:00:08] Mikhail Parakhin: Thank you. Welcome.[00:00:10] swyx: I don't even know if I should introduce you as CTO of Shopify. I feel like you have many identities. Uh, you led sort of the, the Bing ML team, I guess, uh, uh, or ads team. I, I don't know, I don't know, uh, you know, it's, uh, people va-variously refer you as like CEO or, or, uh, I don't know what that, that, that said previous role at Microsoft was.[00:00:29] Mikhail Parakhin: Uh, that was... Yeah, my previous role w- at Microsoft was the-- I actually was the CEO of one of Microsoft's business units, which included, as I, you know, as we discussed, all the things that people like to laugh about, uh, including Windows and Edge and Bing and ads and everything.[00:00:47] swyx: Yeah, yeah. What a, what a, what a wild time.You've obviously, uh, done a lot since you landed at Shopify. Uh, one of the reasons I reached out was because you started promoting more sort of internal tooling, uh, primarily Tangle, but also a lot of people have seen and adopted Tobi's QMD, uh, and obviously, I think, uh, Shopify has always been sort of leading in terms of, uh, engineering.I think more-- it's just more recent that you guys have been more vocal about your sort of AI adoption. Is that, is that true?[00:01:16] Mikhail Parakhin: Well, I think AI tools in general are fairly recent development, uh, and we've-- Shopify, you know, at this stage of its development, we're developing AI in-in-house and other, uh, building tools that use AI and, you know, interfacing with the wider AI community, uh, you know, are on the sort of the, uh, runaway trajectory.So it just did by sort of natural byproduct. We, we talk about it more also. We just, uh, just even yesterday, Andrej Karpathy was famous in tweeting about, oh, are there some, uh, ways, uh, that, that you can organize your agents to store the data and then, uh, look up the data so that you don't have to research or, or lose context every- Yestime. And a little bit tongue in cheek, I tweeted that, “Hey, we've, we've done it much earlier, and we even have different approaches, Tobi and I.” Tobi, of course, is a big fan of QMD, and I'm more of a SQL, SQLite fan. But, uh, yeah, very similar things that we've already done here. The point is, yeah, we're very dynamic, you know, explosively growing company, and we have to be at the forefront of AI adoption, obviously.[00:02:29] swyx: Yeah. Yeah. Um, you, your team kindly prepared some slides actually that we were gonna bring up on to, uh, the screen. I think I can, I can screen share, and then we can kind of go through some of the shocking stats that maybe, maybe put some numbers to what exactly is going on. So here we have, uh- An internal AI tool adoption chart.What are we looking at here? What ?[00:02:54] Mikhail Parakhin: Yeah, this is very interesting statistics. Uh, this is number of daily active workers, you know, think of, uh, DAO, basically the active users of-[00:03:05] swyx: Yeah ...[00:03:05] Mikhail Parakhin: AI tool as a percentage of all the people in the company, right? And then- Yeah ... different AI tools. And, uh, you could see two things here is that one is the green is total.Uh, green is just total. So you could see that it approaches really % by now. It's hard not to do your job now without interacting deeply, at least with one tool. You could see another interesting thing is just as many people commented in December was the phase transition when suddenly models gotten good enough that, that everything took off and started growing.Uh, it, it was many people noticed that the thing is that small improvements accumulated into this big change in Sep- December roughly timeframe.[00:03:52] swyx: Yeah.[00:03:52] Mikhail Parakhin: The other thing I would claim you could see is that, uh, CLI-based tools and tools that don't require you to look at the code becoming more popular, and you could see, yeah, various versions of, uh, Cloud Code and Codex and Pi and internal development tools taking off.Uh, exactly, yeah, uh, and blue is our River, just internal agent for coding, where tools, uh, that require IDEs such as, uh, GitHub, Copilot or Cursor, they're not exactly shrinking, but they're not growing as fast. Like, uh, red, red line is, is the IDE kind of tools. So you could see that they're, they're not experiencing as, as fast of a growth.[00:04:37] swyx: As I understand it, basically, every employee has their choice, right? Of choose whatever tool you use, and then you're just kind of doing a, a daily sur-survey or something.[00:04:47] Mikhail Parakhin: Exactly. And, uh, we- Yeah ... the, the push is to get your job done, you can use any tool, and we effectively fund unlimited tokens for everybody.Uh, we, we do, we do try to control the models that, uh, people use, but from the bottom, not from top. Like we basically say, “Hey, please don't use anything less than Opus four point six.”[00:05:09] swyx: Oh .[00:05:10] Mikhail Parakhin: Some people, some people end up using GPT five point four extra high. Some people use Opus four point six. Um, uh, you know, uh, there are some, uh, there are plus and minuses in going for full one million context window versus not.But, uh, we try to discourage people from using anything less than that.[00:05:28] swyx: Yeah, yeah. Got it, got it. Uh, I mean, uh, that's, you know... The, the next chart here, it really kind of shows the expansion and the sort of December twenty twenty-five inflection, right? That, uh, people are using a lot of tokens. I think it's also really interesting that no one was kind of abusing it in twenty twenty-five.Like it was- Had comparatively, uh, to this year, there was almost no growth. I mean, it's still like, you know, probably, probably gave fifty percent.[00:05:56] Mikhail Parakhin: Yeah. This is just a different scale. It's still exponential- Yeah, yeah ...growth at just a different- ...rate of expansion. Uh, there was inflection point, and Sean, I would claim the, the super interesting part here is that you could see that the distribution becoming more and more skewed.Yes. The top percentiles grow faster. So that means- Yeah ...the people in the top ten percentile, they, their consumption grows faster than seventy-five and so forth. So, uh, the distribution skews more and more towards the highest users, which is... I don't know what it tells me. It's like it feels not ideal, to be honest.Or maybe it's okay. We'll see.[00:06:36] swyx: Why does it feel not ideal? Is, is it because of, um, quantity over quality, or what's the concern?[00:06:42] Mikhail Parakhin: Because take it to the limit. That means, you know, if, if this rate of separation continued- Ah, yes ...a year, there will be one person consuming all the tokens. So it's just, it's kinda strange.[00:06:54] swyx: Yeah, I mean, um, uh, I, I think internal like teaching and all that, uh, will, will help sort of distribute things more widely. But in, in the early days, of course, the people who are sort of more AI-pilled will obviously find more ways to use it than the people who are less AI-pilled. Maybe let's, let's call it that.I'll just, I'll just kinda quickly, uh, pause from the, the... You know, we will go back to the rest of the slides, but I just wanna, um, review, you know, there are a lot of CTOs of, of large companies like yourself where they're all considering some kind of token budget, right? Like I think it's something, something that Jensen Huang has been talking about, where like if your 200K engineer is not using 100K of tokens every year, like they're, they're underutilizing coding agents.Of course, Jensen Huang would say that, but like it seems a very quantity over quality approach and like some, some people are basically saying like, well, is this comparable to judging engineer quality by lines of code, right? Which we also know is like kind of flawed, but better than nothing. So I, I don't know if you have like a sort of management take here on, on how to view this kind of, uh, metrics.[00:08:02] Mikhail Parakhin: Well, I mean, you're, you're baiting me. I, I like... This is my favorite topic. Uh, if you let me, I'll probably talk for two hours on just this. I have a lot of things to say. Like I do think Jensen gotten a lot of bad press saying, “Oh, of course you're, you know, this, uh, the- ...the cake seller says you don't need enough cakes.”You know? Like, of course. Uh, but, uh, I actually, uh, think that's undeserved. I think he, he's actually right. Uh, I do think- He,[00:08:33] swyx: he's directionally correct.[00:08:35] Mikhail Parakhin: Yeah. Yeah. He's directionally correct for sure. Uh-[00:08:37] swyx: Who knows what the right number is? Yeah.[00:08:39] Mikhail Parakhin: The thing that I do Uh, want to say, and this is something that we learned through trial and error and very important is like two things.One is that it's not about just consuming tokens. Uh, you can consume tokens and, and in fact, the anti-pattern is running multiple agents, too many agents in parallel that don't communicate with each other. That's almost useless, uh, compared to just fewer agents and burns tokens very efficiently. Uh, setting up the right critique loop, especially with the high quality models, where one agent does something, the other one, ideally with a different model, critiques it, uh, suggests ways to improve it, the agent redoes it with this critique and, and so it takes much longer.So people don't like it because latency goes up. You know, they, they have to wait until this debate is happening. But, uh, the quality of the code is much higher. And another thing, just since you mentioned like, look, uh, uh, yeah, the overall budget is just like, uh, lines of codes. Lines of codes are exploding for everybody right now, or partially because AI is really mover balls, but partially just because AI can write a lot more code, you know, doesn't get tired.And so you have to have to have a very strong narrow waist during PR review. Otherwise, just the number of bugs will go through the roof. It's, uh, it's this unexpected consequence of the just volume trumping everything. I would claim by now good model writes code on average with fewer bugs than, than the average human.But since they write so much more of it, like more of it will make it into production. So you have to- You still[00:10:26] swyx: have[00:10:26] Mikhail Parakhin: more bugs. Yeah. Have to have a very rigorous PR reviews, also automated of course. But, uh, yeah, that to spend a lot budget there. Like this, this for me, for me, actually, the important metric is the ratio of budget spent during code generation versus, uh, spent, uh, expensive tokens like GPT, uh, five point four Pro or, uh, uh, Deep Think from Gemini, you know, checking on PR reviews.[00:10:55] swyx: Yeah, totally. Uh, I noticed in your chart you didn't have any review tools. Do you just use like, like let's say a Claude code to review tools? Or do you have another set of review tools like the Greptiles, the Code Rabbits, uh, Devin Reviews has a review tool. I don't know if you've had those specialist review tools.[00:11:13] Mikhail Parakhin: You are a little bit jumping on my store tool right now because the graphs I was only showing public tools. Uh, uh, the-- I haven't found a good PR review tool that, that does what I think should be done. And, uh, partially my, my thinking is because it's so... It just goes against both what people feel like emotionally they prefer and, uh, some of the, uh, you know, frankly Even business models that, that the companies run.At peer review tool, uh, time, you want to run the largest models. That means, I don't know, Codex or, or, uh, Cloud Code is not gonna cut it. You need to have pro-level models if you really want to, uh, stand the tide of bots from going into production. And you need us to spend a lot of time, the models taking turns, but you don't want, like, a big swarm of, uh, of, uh, agents.So in fact, you end up in a different dual-dualistic world where you generate not that many tokens. You, in fact, generate few tokens, but it takes f-a long time because these are expensive models taking turns rather than many, many agents trying to do many things in parallel. So that's, that's why I feel like I haven't found good tools, so we are using our own for peer review for now.[00:12:33] swyx: Yeah. Yeah. I mean, uh, I think a lot of companies are building their own, uh, especially to their needs, right?[00:12:38] Mikhail Parakhin: Mm-hmm.[00:12:38] swyx: Um, I, uh, you also have a chart here going back to the slides on, uh, PR merge growth, where we're now at thirty percent, uh, month on month rather than ten percent. Uh, and also the, the estimated complexity is going up.You know, this is productivity, right? ‘Cause y- presumably there's more stuff going into the code base and more, more features getting worked on. I'm curious about the backlog, right? Like the, the, the-- I actually don't mind a pro-level model taking an hour or two hours to review my PR, because I've dealt with humans who take a week to review my PR, right?And I keep pinging them on Slack, “Hey, hey, review my PR.” So, you know, I think there's some trade-off here where, like, it still doesn't make sense.[00:13:18] Mikhail Parakhin: Exactly. That, that's exactly m-my point. Uh, that on one hand, you can tolerate longer latencies at, uh, PR. On the other hand, like right now, the real problem is not in spending time waiting for PR.It's real problem is since there's so much more code than- Yeah ... uh, probability of at least some tests failing going up, and then you, like, keep de-failing, then you have to find the offending PR, evict it, retest it without that PR, and so deployment cycle becomes much longer. Uh, so it actually, in terms of the overall time to deploy, it's total time savings if you spend more time on a longer model, like thinking for an hour, because then, then you, you don't have to spend all that time during testing and rolling, you know, rolling back the deployment.[00:14:03] swyx: Yeah, totally. That's still worth it. You know, you don't look at the individual, look at the aggregate, and look at the, the, the change in the aggregate system.[00:14:11] Mikhail Parakhin: Exactly.[00:14:11] swyx: I'm kind of curious if, like, there's this PR mentality and, like, c-- the, the, the CICD paradigm will be changed eventually. Some people are like, obviously a lot of people want new GitHub, but I even wonder if, like, Git is the problem, right?Like, is that the bottleneck? Is the concept of a PR a bottleneck? Do you guys use stack diffs? I don't know if, uh, that's a, like, a merge queue stack diff type of thing.[00:14:34] Mikhail Parakhin: We, we use, we use Stacks, we u- we use Graphite. We worked with, uh, Graphite a lot. Uh, so we use Stack, uh, PRs. I think, uh, like that's clearly the overall CICD in general, and the interaction with the code repository right now is the, clearly the sort of the, the main issue and the bottleneck for us, uh, and highest top of mind.I would say we probably need a different metaphor or different whole design of how to process it in new agentic world. I haven't seen anything dramatically better yet. I, I think everybody right now is just trying to keep their head above the water ‘cause, ‘cause there, there's so many PRs and then everybody's CICD pipelines start creaking, the, the times are increasing, the number of bugs slipping by increasing, and you have to, have to clap on down.And so we are a little bit in this situation when we need to first stabilize that story and then start thinking, hey, what, what it could be a completely different and new world, which I haven't... I know some people working on it. I haven't seen something, like anything super compelling yet, but clearly the old thing were designed for humans will need to be morphed into something new.[00:15:53] swyx: One of the thing that I, I think about is kind of like the merge conflict is basically a global mutex on the whole system, right? And in, in hu- in human organizations, we do have something like that. It's the company standup. But like, other than that, it's like it's actually fitting for us to be somewhat decentralized, somewhat plugged into one stream of information source, but somewhat lossy.Like it's okay, you know, that, that not every delivery is like atomic consistency. Like we're not dealing with a database sometimes.[00:16:27] Mikhail Parakhin: This is a very good point, uh, because since humans don't write code too fast, you know that global mutex is not too bad. Once you-[00:16:36] swyx: Yes ...[00:16:37] Mikhail Parakhin: start writing code at the speed of machine, it becomes the, you know, the bottleneck.Then what do you do? Maybe, and I can't believe I'm saying this because I, I'm long-- lifelong opponent of, uh, microservices, and I always thought that was, like, a really bad idea. And now that you're saying it, like, maybe in new guys like microservices will make a comeback, you know, because then you, you can ship things independently in tiny things and, and the managing all that complexity automatically will be much easier.I don't know. Like, we'll s-- we'll have to see.[00:17:10] swyx: Yeah. I mean, I don't know what the Microsoft or, or Shopify thing is, but I, I read this paper from Google where they have a monorepo that deploys into microservices, right? And then, uh, the other concept that I think about a lot is the Chaos Monkey concept from, from Netflix.Being able to create, like, this robust system where, um, uh, you know, you, you have the service discovery, you have the, uh, the independent, independent microservices discovery and, and, uh, you know, probably going to be a fair amount of duplication. That's how an organic system sort of scales, uh, that, that you have that...I don't know how you call it. Slack? Robustness? Depend-- uh, d-duplication. I, I, I forget the-- I, I'm-- And this-- those-- these are not exactly the terms- Hmm ... I'm looking for, but I c-can't really think of the words. Okay. I was gonna go into Tangent and Tangle. Uh, so, uh, we, we sort of discussed the overall stats that, uh, Shopify has.Uh, but, you know, I, I think some, some pretty cool stuff that you guys are working on is your ML experimentation, uh, and your, your sort of auto tr-research training pipeline. Presumably you're much closer to this one because it's, it's a sort of personal hobby of yours. How, how would you explain them in, together?I thought we have a slide that, like, uh, has the s- the system diagram.[00:18:24] Mikhail Parakhin: Yeah. Tangle first and then Tangent as a-[00:18:27] swyx: Yeah ...[00:18:28] Mikhail Parakhin: as a thing on top of Tangle. And, uh, Tangle is the third generation, I claim, of, uh, systems of, uh, running any data processing, but a bit with a skew for ML experiments, but not necessarily. Any sort of data processing tasks where you need to iterate, share, and you have scale so that you want maximum efficiency.You know how, like, normally you would work, you would-- Imagine you're a data scientist or an ML practitioner, you would get Jupiter notebooks or, or maybe you would get, uh, you know, Pyth- your Python scripts, and you would manage the data, and you produce those TSV files, and you put them in some JFS or something.Then you would notice that, oh, it has this, uh, weird missing values. You go and write another script that, uh, goes and replaces them with, uh-[00:19:20] swyx: Ah ...[00:19:21] Mikhail Parakhin: dash S. And then, then you, then you run some, some, uh, “Oh, I need to filter bots.” And so you run some light GBM model that, uh, removes the bots. And then, then you like-- And then you, you kind of like get into shape, and then you start experimenting, and you run multiple experiments, and then you're like, “Oh my God,” like, “this experiment is worse.”You undo, and you cannot get to previous result. And like, “Ah, what did I do?” Like that. Again, then, then you finally like get everything working. Then you like start throwing it over the fence to production. You, you replicate it, those things don't work, and then sometimes you like don't notice that you forgot some feature naming and the, the features don't match.But then, like imagine you, you did everything, and then six months later you're like, have to repeat it because now there's more data, or you wanted to do another pass, and you're like, “What, what did I do?” Or like, or like, “This script crashes now,” or the, “the path has changed.” And then, then you're trying to, like you spend another month just doing ar- digital archeology on your own, you know, history, right?Now multiply that by many, many teams. Now imagine you got an intern that you wanna ramp up. Now you have to show that intern, “Oh, you know, look, here's the folder, there's the scripts, you know, ask your cloud agent to do, and then, uh, to, to figure it out.” And then cloud agent does something, and then you're, “Ah, yeah, right, right, it was the wrong folder.I forgot to tell you, I actually have this other thing I forgot myself.” And, and that's, that's the, like, the daily life we all, uh, all know it, uh, if, if you're a data scientist, machine practitioner, ma- machine learning practitioner or, uh, or even like any data managing, uh, person.[00:21:00] swyx: Yeah. So I, I used to do this, uh, f- uh, on the quant finance side, uh, in, in my hedge fund.So we did this before Airflow, and then, uh, obviously Airflow came along and, uh, then more recently Dagster, uh, I would say is like, in my mind, what I would use for that shape of problem, uh, where you had to materialize assets and create a pipeline.[00:21:19] Mikhail Parakhin: And that's, that's very good segue because... So Airflow is great, but Airflow is more about you, you have something and you wanna repeatedly run it in production on schedule.It's less about you as a team developing things and being able to share, and you grabbing the standard pipeline and saying, “Hey, I wanna change this tiny little component in the huge sea of data processing, and I don't wanna-- I wanna run ten experiments on this, and I wanna do hyperparameter optimization.”All that is very hard to do with Airflow. It's very easy to do with Tango. Tango is m- more about, it's everything about group of people Running experiments, it might be agents too nowadays. Uh, running experiments cheaply, collaborating, sharing results. Uh, you don't need to understand fully. You, you grab-- you clone somebody else's experiment or somebody else's pipeline, uh, run, uh, change small piece, run it, be, like, get it to production state, and then ship in one click.So then the... You don't have to port it into any other system to, to run in production. You can just run the same experiment. It's, it's fully production ready. And, and it's, uh, it has lots of... Again, as I said, it's third generation system. The original one was, I would claim there was Ether and then, uh, at least in my career, Ether was the first, first, uh, that pioneered this type of approach.And then there was, uh, Nirvana, which, uh, uh, at Yandex, which did kind of sec-second take on this. And now this one aggregates the, the learnings from all of those and, and Airflow as well to, to get to the state where you try it, it, it feels kind of magical. Uh, ‘cause now everything is based on content, uh, hashes.So even if the version changed, but if the output didn't change, nothing is being rerun. It's very efficient. If you... Multiple people start experiment that needs the same sort of data preprocessing, it's not repeated multiple times. It's automatically done only once. If you start ten experiments that all require, you know, some, some data preparation first as the first step, and you don't have to coordinate for that.Like, you don't have to know that other people are starting it. You now, it's very easy compos-, uh, composability, any language you can u- uh, you wanna use, and it's very visual. So you can see immediately, you can edit it easily, you can assemble small things with just even mouse clicks if you want to, and, uh, share, clone.And everybody knows also it's fully kind of static in the sense that we rerun it second time, it will exactly have the same results. Like, you will never have to do digital archeology. So full versioning and everything is also there.[00:24:06] swyx: Uh, so, so people can, uh... It's open source. Go to the GitHub repo and, and, uh, check it out.Uh, and it is also a really good, uh, blog post about it. I think all these is, like, really appealing. The, the, the, the thing that I think sells me the most about it is that, um, sort of development to production transition, right? Which I think, um, a lot of people haven't really solved that, uh, strictly, right?Like, we develop really, really well in, in Python notebooks, but then, you know, that's obviously not a sort of production ready process. I think that, like, any way in which that is solved, I think is, is very appealing. Then the other thing that you mentioned, which also raised my eyebrows, was content-based caching, which you mentioned is, is, um, you know, is ve-very much, uh, um, a sort of efficiency measure about, uh, you know, just like recalculation only on, on sort of content addressing Which I think makes sense.Uh, it surprised me that the savings could be this much, but maybe I just haven't worked at your scale where there's so much duplication, uh, that people just rerun because they change a single ID upstream.[00:25:10] Mikhail Parakhin: It does, yeah. But it's not only you rerun. The, the main savings are coming from the fact that you ran it, you got your job done, and you moved on.Then- Yeah ... somebody else in some department you don't know existed runs the same task, but on a newer version.[00:25:27] swyx: Yeah.[00:25:27] Mikhail Parakhin: Like right now, you can't, in, in most of the organizations, you can't even find out about it so that you can't even measure that you're spending that time twice, right? Here- Yeah ... if everybody's on Tango, that's detected automatically and detected that the output is the same.And then for that person, all it looks like is like experiment just suddenly moved, jumped forward, right? Uh, uh- Yeah ... so that's because, because the, there's network effect of multiple people helping each other.[00:25:51] swyx: Yeah. This is one of those things where it's designed to be a platform from the beginning rather than an individual developer's tool from the beginning, right?And, and everything's gonna streams down from there. That is the sort of Tango, uh, orchestrator, and it's, it manages jobs. We've seen a few versions of this, and this is obviously, uh, uh, the sort of, uh, unique approaches that you guys have, have, uh, figured out. And then there's Tangent.[00:26:14] Mikhail Parakhin: Yeah. And Tangent is basically an automatic auto research loop that can help and kind of do your work for you.Uh- ... you know, uh, effectively, effectively, Andrej Karpathy recently popularized it with auto research. Yes. Remember he said like he was, uh, speed running this, uh... Yeah, uh, you know the story. The, here we're basically bringing the same capability into Tango so that, uh, the, uh, Tangent can analyze it. It's just an agent that can run multiple experiments, figure out what can be changed, and keep on rerunning it, keep on modifying until, uh, maximizing some goal, some loss function, whatever you need to, to achieve.And in general, I would say if you're not using auto research-like approach in whatever you do, like literally whatever you do, then you're missing out. We saw at Shopify that taking like a wildfire, anything where you can put measurements can be done dramatically better. Our-[00:27:19] swyx: Mm-hmm ...[00:27:20] Mikhail Parakhin: uh, speed of, uh, templatization HTML, uh, completely new UX tem- uh, templatization of, uh, reducing latency for liquid themes.Uh, we-- Our, uh, search, uh, recently we moved from It's hard even, uh, quote from eight hundred QPS to forty-two hundred QPS with the same quality just by pure optimizations and not a research loop that kept running and changing code in our index serve on the same number of machines, just increasing the throughput.We, we managed to improve the quality of gisting and machine learning process. Uh, you know, gisting is the prompt compression technique that[00:27:59] swyx: allows for[00:28:00] Mikhail Parakhin: lower latency and, and lower and, uh, actually higher quality slightly. So like literally whatever different walks of life, and it doesn't have to be AI related.Uh, we, we had a reduction in, uh, storage because the agents would go and find data sets that clearly are derivative, uh, and then you don't need to store things twice. You know, we, we, we found somewhat embarrassingly that it was one of the largest tables was hashing random IDs into another random ID, and we literally- Oofput only one. So it was translating, yeah, two random IDs hashed[00:28:36] swyx: into[00:28:37] Mikhail Parakhin: each. So, so[00:28:37] swyx: it has access to the code as well, so it can, it can check the, like what, what the hell is it doing?[00:28:42] Mikhail Parakhin: So there, there cou- it could be run in two levels. You, uh, you know, at the superficial level, it could just use ex-existing components and, uh, reshuffle them.Uh, you know, like you can grab- Yeah ... uh, XGBoost, and you can grab some, some Py- PyTorch module, and then can grab some, you know, grab another tools and, and combine them. At a deeper level, since Tangle is all sort of CLI based underneath you, every, every component is a wrapped really CLI, uh, call and a YAML file, it can analyze code and create new components and, and, uh, keep on iterating as well.So, so you can, you can both have quick modifications of existing t- uh, pipelines with the, with components that are already there pre-baked, or you can create new components, uh, and-[00:29:29] swyx: Yeah ...[00:29:29] Mikhail Parakhin: keep iterating on those. So auto research is, again, this is probably the, the thing I was excited the most in the last two months happening, and we see it taking like, like totally like a wildfire.Just, uh, everybody, every day, every... well, every day, every minute, I would, uh, have somebody Slack message saying, “Oh, look how much better I made it.” And, uh, it's all throughout the research.[00:29:53] swyx: Is this democratized in some way in, in the sense that like is it your ML, uh, engineers and researchers doing this, or is it your regular PMs and software engineers also have the ability to auto-- to use Tangent?[00:30:07] Mikhail Parakhin: This is an awesome question. Like, Tango in general and Tangent in particular are extremely democratizing. Like they- Yeah ... they are the main tools for- ‘Cause I don't[00:30:15] swyx: need the details.[00:30:16] Mikhail Parakhin: Yeah. Exactly. Initially used by ML and AI engineers, but then literally, as you said, PMs are like the highest user right now is one of PMs on our org, uh, Sartak and he was, he was number one by, by usage of, of this ‘cause they're just, uh, energetic and knowledgeable, and now it, it unlocks a lot of capability where you don't have to co-change code manually.[00:30:39] swyx: I mean, I mean, because it kind of cuts out the ML, ML engineer from the process because the, the, the PMs have the domain knowledge and the ability to think about, uh, from first principles about, okay, what, what results do I want? And they can-- they even have the access to the data that, that needs to go in.So it's like in some ways, like this is the magic black box that we've always wanted for, for training and, and for, uh, I guess, uh, uh, hill climbing, whatever.[00:31:04] Mikhail Parakhin: It's basically cloud code for your AI development- ... uh, situation, right? Like now, now you don't have to know exactly how algorithms work. You can just, uh, bring your domain knowledge and expertise and product knowledge and iterate within Tangent until you've gotten the results that you need.[00:31:21] swyx: In my previous roles, every time that someone has pitched AutoML, you know, I've always been like, “Uh, this is not, this is not gonna work. It's, you know, it's, it's always gonna be a flop.” Somehow it's working now. I mean, presumably the answer is now we have LLMs and it's good enough, right? It's, it's an emergent property that we can do auto research, but like, it doesn't feel that satisfying that how come we didn't do this before, right?Like we just did like parameter search and like, I don't know. That's maybe that's it.[00:31:48] Mikhail Parakhin: Yeah. Bayesian optimization and hyperparameter optimization was, was the one that, or facet of AutoML that was used very actively, which incidentally also built into, uh, Tango. But, you know, I know Patrice Simard very well, and, uh, he was such a, uh, such a proponent of AutoML, and he put, like literally spent careers trying to democratize it.Without LLMs, it just turned out to be very hard. Like it, you, you would have flexibility within certain narrow domain, but it was hard to wider scale, and now with LLMs suddenly it's like magic wand, and so suddenly everybody- ... is an AutoML expert.[00:32:28] swyx: Yeah, I, I think it's multiple things, right? Like I'm, I'm just gonna bring up the, the, the chart again, right?Like LLMs can do the monitoring very well. That is the very potentially unbounded, super unstructured. It can do the analysis very well, it can do the... Uh, and basically it is much more intelligence poured into every single step. Uh, there's maybe nothing structurally changed about AutoML, but this is just m-more intelligent and more unstructured.[00:32:53] Mikhail Parakhin: Exactly.[00:32:54] swyx: Any flaws that you've run into? Like everyone is like drinking the Kool-Aid, oh my God, time savings, uh, you know, performance improvements. Like what, what, uh, issues have you have, uh, come up?[00:33:06] Mikhail Parakhin: This is really cool. It's not a solution to all the world's problems for sure. The limitations are usually the ones I-- And this is where we get into a bit of a subjective territory.Uh, I can only share what I've, I've seen so far, and I'm sure the situation, uh, is changing, and, you know, maybe after I say it, like many people will reach out and say, “Hey, what about this?” And you don't know that, and then, then we'll be probably right. But what I've seen is auto research is very good at doing kind of obvious things that you don't have bandwidth to do or you didn't notice or maybe you're not aware of like the-- some standard practices.It is not good at doing something completely out of distribution, something that, you know, you have to think for, for multiple days, uh, and, and do something like none of this. So, so it's, uh, I, uh, set an experiment once, uh, on, on my sort of, uh, hobby thing, and I let it run for, uh, ended up, uh, several weeks run, uh, you know, it's like full production kind of scale, so it, you know, slow runs and, and it ex-- it performed in the end, uh, over four hundred experiments, and only one was successful.I'm like, “Okay, that's, that's good.” But-[00:34:18] swyx: But it saved time.[00:34:19] Mikhail Parakhin: Yeah, I saved time. Like it, it was the, that thing. Yeah, if I, if I were doing four hundred experiments myself, my betting average, as I said, would have been much higher, I'm sure. But also, first of all, it would take me like three years to do four hundred experiments.And, uh, I didn't have to do them. Like the machines were just, uh, the price of electricity did that. So, and I got one improvement, uh, that in, uh, my, my-- Honestly, when I was starting that experiment, my thinking was to go and show that, “Hey, Andre, maybe you just don't know how to optimize.” And I was super smart because in, in my pro-problem, it was optimized for many years, and it was like fully improved.Uh, and I didn't expect it, you know, auto research to find anything at all. Yet it did. So instead of making fun of Andre, I ended up, uh, a big, big supporter. Yeah, that's exactly the tweet. Yes.[00:35:10] swyx: You and Toby really, really go back and forth on-online a lot, which is really funny. Uh, think of it as, as an eval for the optimalness of the code it's running on.Uh, it's almost like it reminds me of like a Kolmogorov complexity thing, but, uh, I guess it's-- there's some optimal thing that you're trying to sort of reduce down to, I guess. Um, and so, so you, you, you know, you should congratulate yourself that you had, uh, you know, uh, ninety-nine percent, uh, optimality.[00:35:36] Mikhail Parakhin: Exactly, yeah. I think Andre really deserves a lot of credit for popularizing this approach. This is, uh, this is incredibly, I think, powerful and cool and You know, the, uh, even him, him just mentioning it led to a lot of gains in a lot of places in the industry, so we should be thankful.[00:35:56] swyx: Yeah. I think he also has a just...I don't know what it is. Like, um, you know, it, it is a simple self-contained project that people can take and apply to other things, which is, is, is one thing, but also just the name. Just like somehow no one, no one managed to call their thing auto research. It's just naming things is very important. I think that that is mostly, uh, our coverage of Tango and, and, uh, Tangents.I think obviously, you know, there's a lot of, uh, ML infra at, at Shopify that people can, uh, dive into. We're about to go into SimGym, but before I do that, any, any other sort of broader comments around this whole effort? Like where is it, where is it leading to?[00:36:36] Mikhail Parakhin: As a segue to SimGym, like all those things start composing strongly.And, uh, you could see a huge unlock when you can look at each one of the tools and, and you see, oh, they're extremely useful. Uh, Tango is useful by itself. Auto Research is useful by itself. SimGym is useful by itself. If you combine all three, you create like synergetic effect. I think that's why we wanted to even, uh, cover them today is because this is something that if you go back even, you know, five years ago, would've been unthinkable.Uh, replicating that, uh, would, would be either incredibly costly or impossible, right? With probably thousands of people are required.[00:37:20] swyx: Well, we have serverless human, uh, serverless intelligence, right? Like, uh, so yes, you do have thousands of hu-- of, of intelligences, not just, not humans. And that's, that's close enough, right?Even if they're not AGI, they're, they're close enough to do the, the task that you need them to do. And, and, you know, that's, there's plenty for, for a lot of routine work, knowledge work. Okay, let's get into SimGym. Um, this is one of those things I, I was surprised to see actually it's apparently your, uh, one of your most popular launches, and I think something that, uh, I think Sim AI, I think Yunjun Park, who did the Smallville thing, there's a very small cottage industry of people trying to do like the simulate customer thing.I think a lot of people maybe don't super trust this yet because they're like, well, obviously they would just do what you prompt them to do, right? But maybe just think, uh, tell us about the sort of inspiration or origin story.[00:38:10] Mikhail Parakhin: That's exactly actually the thing I wanted to cover, because if you don't have the historical data, all you can do is prompt a-agents in a vacuum, and they will do exactly what you prompt them to do.In fact, when I first proposed it, and this is a bit of, um, my brainchild initially, if I, I can boast, even Toby said like, “But wouldn't they, they just repeat what, what you tell them?” And, uh, but I'm like, “Yes, except Shopify has decades of history of how people made changes and what there is, uh, there, what it resulted in terms of sales.”So now what we can do is we can-- we have this... It's not, it's a noisy data. There's a small, usually websites, uh, you know, like things, things are never in isolation. It's almost never AB experiment. It's always AA experiment when there's has two meanings, but basically, you know, in different time you run two different things.But if you aggregate in general, uh, like everything together, and you apply, uh, denoising and collaborative filtering like approach, you can extract a very clear signal. And then you can optimize your agents. And that's why it took so long. It took almost a year of that optimization of just us sitting and fiddling, and, and we had this internal goals of correlation of hitting-- internal goal was to hit zero point seven correlation with, uh, add to cart events, for example.Like that, that if we run real AB test experiment, that it should, it should go and, and rep-uh, replicate, uh, same sort of success that, that humans had or lack thereof. And it, it took forever, and I don't think that's easily replicatable because, uh, like who else would have that data? You have to have this historic, you know, decades, uh, worth of data.And now, now the, like the other thing you need is in-infrastructure and the scale, right? Because, uh, w- again, what we found, uh, stat sig results, you need to run a lot of simulations, a lot of agents, and, and it's-- Those are expensive things. Like you're, you're making actions in the browser because you want a real friction.You want to, to be able to get the image like of what humans will see because you wanna, uh, detect effects like, “Hey, if I make my images larger, will I have more sales or l- uh, fewer sales?” And like usually people's intuition here, by the way, is that I increase my images, I will have more because they look nicer.You know, designers all look sparse and big images. Like usually your sales tank, right? But, but, uh, you know, from HTML, all the characters look the same only the, the size tag looks different, right? So it's very hard. So you have to take visual information, you have to run this in simulated browser environment on the big farm and, and of course, you have to have, uh, like very, very expensive model, good model with multi-model model.So all this it's-- is what's taken so long and, uh, to share my personal fail a little bit there, Sean, is like, you know, we always had this bias to-- for like large company bias. You know, we always, uh, whenever you-- we do, we're like, “Hey, we'll run an experiment,” right? We make, make a change, and we will run an experiment and then, uh, see, uh, see which one's better or like, “No, this is worse,” and most of them are worse, so you discard it and keep iterating, hill climbing.And we're like, “Oh, like smaller merchants, they cannot get stat sig results. They cannot really run experiments simply because, you know, in a week there would be not enough data for them.” So we thought from this perspective. What we didn't realize is that most people don't have A and B, they just have one thing, and they need suggestions of What A and B should be.So, uh, we first build this, hey, we run simulation on two separate teams and, and, uh, say, “Hey, which one is better?” We then morphed it into, and very recently just released it, when you have just your site, your theme, we run over it and we say, “Hey, here's what predicted values of, of, uh, uh, conversions are, and here's how we think you should modify it to increase your conversions.”And then circling back to what you started with, the proof is in the pudding. Like, if we are not correlating with reality, like, people will not be using it. And, uh, thankfully, we see literally every day more users than the previous day. So, so right now, uh, right now- It's working. Yeah. I'm-- Right now my problem is how to pay for it all because the so our major thing is how to optimize the LLMs, do distillation, how to run the headless browsers, uh, and handful browsers, uh, uh, cheaper so that we can accommodate the increase in traffic.[00:42:47] swyx: Yeah. I, I understand that you, uh, you published a lot of technical detail at GTC, so I was just gonna bring it up a little bit. I think s- was this in, in con-conjunction with some kind of GTC presentation? Or something like that, right?[00:42:59] Mikhail Parakhin: Well, we, yeah, we, we did it in several place, but yeah, we had the engineering- Yeahblog, uh, as well. Yeah.[00:43:05] swyx: Yeah. So you're running, uh, GPT OSS. Uh,[00:43:08] Mikhail Parakhin: the, this is an older version. You know, now we run multimodal model. But yeah- Yeah ... GPT OSS, we still run GPT OSS as well for[00:43:15] swyx: And then you have the VMs, and you also have browser-based. I really like this one where it you said, “It violates almost every assumption that standard LLM serving is designed for.”And then you had like, basically orders of magnitude differences between everything.[00:43:29] Mikhail Parakhin: Exactly. Which is, which, uh, which was, you know, a bit of a challenge to implement, like when, like even simple things. Uh, be- since it violates all the assumptions, for example, multi-instance GPUs, like MIGs don't work as well.But we needed, uh, to get MIG to work because, ‘cause otherwise it's way too expensive. And so we had to deal with the, yeah, with, uh, lots of infrastructure and, and, uh, work with, uh, uh, Fireworks and CentML, uh, you know, to help with optimizations and browser-based, as you mentioned. Yeah, like, takes a village.[00:44:04] swyx: Okay. So there's a lot of like, I guess, experimentation in the infrastructure so far, and you've published more or less what you have here. I guess I'm, I'm less familiar with CentML. I, I don't do, uh, that much work in this, this part of the stack. But why was it the sort of preferred instance platform?[00:44:22] Mikhail Parakhin: There are really three probably top companies. There used to be, uh, uh- Three top companies, uh, at least I was aware of that did, uh, LM optimization. You know, together Fireworks and Santa ML, not necessarily in that order. Santa ML recently got acquired by NVIDIA. Uh, what they did is if you have a model and you want to optimize it to a specific prof-- uh, profile of usage, uh, they would go and do it.And, uh, we work with, with those companies, uh, this was work particularly in with Santa ML and NVIDIA to get them the best possible results out of it. And, and sometimes you, you have to retune depending on, like sometimes you want the maximum throughput, sometimes you want minimal latency, sometimes you want like the cheapest, right?And, yeah, or some combination. And so yeah, these are people who would come and help you.[00:45:14] swyx: I see. I see. Yeah, yeah. I'm familiar with these people for the LLM, you know, autoregressive stack. But the other interesting category of these optimizers is also the diffusion people, whereas like Fel and, you know, uh, Pruna recently has come up a lot as well, which I think is like really underappreciated, uh, at least by myself, because I, I thought, oh, all the workload would be LLMs, but actually there's a lot of diffusion as well.[00:45:38] Mikhail Parakhin: Exactly.[00:45:38] swyx: There's a lot here, so I, I, I... it's, it's, uh, it's, it's, it's hard to cover. But I, I do think like people underappreciate the importance of customer simulation, basically. I think this is something that I'm candidly still getting to terms with. Uh, you know, uh, you also-- your team also like prepared this, like, really nice diagram.Uh, I, I assume this is AI generated.[00:46:00] Mikhail Parakhin: Yeah, it looks-[00:46:01] swyx: Maybe it's not.[00:46:01] Mikhail Parakhin: Yeah, it looks, uh, Gemini-ish. Yeah, but, uh, uh, honestly, I, I don't know where, where the hell they generated. It looks, look, uh, looks like it's, uh, Google. But the interesting part, John, that, that, uh, we haven't covered, but I, I wanted to mention is if your store had previous customers, rather than it's a new store, you're like new merchant just launching things, it helps tremendously in just correlation and forecast.Yeah, we take your previous, uh, customer's behavior, and we create agents that replicate those specific distribution of, of customers that you get, and then we a- we apply those to your changes, and then that, that raised raw, you know, the re-- uh, just correlation with the add to cart events or to-- with conversion or whatever it, it, it may be, uh, quite dramatically.So, uh, replicating humans in general seems like an interesting, cool challenge.[00:46:58] swyx: As a shareholder, I think this is the-- like if people are Shopify shareholders, they should really deeply understand this because this is basically the moat. The, the more you use Shopify, the more it will just automatically improve, right?Like you're, you're doing the job for them.[00:47:13] Mikhail Parakhin: Yeah, that's what we started with. Like, uh- ... uh, otherwise, if you're just a startup, I wouldn't do it if, uh, you know, if it was my startup because Without the data, it, yeah, as, as you said, it's, it's exactly the case that, uh, whatever you say in prompt, that's, that's what the agents will be doing.[00:47:30] swyx: The statistician in me wants to like really satisfy the sort of, um, statistical intuition, I guess. Um, to me it's kind of, uh, the, the word that comes to mind is, um, ergodicity. Uh, so let's say a, a customer takes this path, customer takes this path, customer takes this path, right? Um, the... In my mind, the way I explain it is like, okay, here, here's the ninety-five percentile, here's the five percentile, and here's the median, right?Um, but to me, what SimGym is potentially doing is that it can, uh, modify... It can sort of model the sort of in-between sort of journeys as well, that, that maybe are dependent on the previous states. This may be like a very RL-type conclusion where like basically the summary statistics, if you only did naive AB testing, you only have the, the statistics at, at, at a certain point, and you only judge based on the sort of overall summary statistics.But here you can actually model trajectories. Does that make sense? Or-[00:48:31] Mikhail Parakhin: That makes total sense because like, well, that, that makes even more sense that maybe even you realize bec- because-[00:48:38] swyx: Okay. Please,[00:48:38] Mikhail Parakhin: please. Yes ... we do-- Yeah. The, so internally, uh, we have this system, we talked about it briefly once at NeurIPS.We have a huge HSTU-based system that models the whole companies, uh, and their possible paths. And like- Yeah ... what you are, what you are showing, like actually at any point of time, you can either model the user's behavior or you mo- can also think about, uh, the whole merchant as a company, as the entity that acts in the world.You can model that as well. And then you can do, can do counterfactuals. In your graph, like in your blue graph, uh, if you're... Imagine in the center there, uh, somewhere in the middle, you would have an intervention. I give that person a coupon, or I don't know, I send a personal thank you card, or give a discount in some- somewhere.And then you can, uh, then you can do forward rollouts from that counterfactual. So what would have happened with that intervention or without the intervention? And you can even ch- change where that intervention, uh, in time can happen, right? Like some- where, where in this journey. So we, we do this at the Shopify scale for our merchants, and then if we notice that something that they can be fixing, like there's a strong counterfactual, like we have Shopify policy, they basically get a notification like, “Hey, we think your...something is wrong with your-” I don't know, Canadian sales. Like, uh, it looks like it's misconfigured. Here's what you need to do. Or do you think like, uh, you have to set up this campaign with these parameters? And we do that at the buyer level to literally offer discounts or cashback or, or things to buyers.So this is-- I'm getting very excited. Like this is my sort of area of, uh, interest, I guess, and, and hobby. But being able to m-model something complex as human beings or companies and model counterfactuals on it, where you can have interventions in the future and optimize when to make intervention, what kind inter-- uh, what kind of intervention to make.It's such an unlock that previously was completely impossible. Like the-- it was, it was always dreamed of, but never... Like how would you even simulate it without LLMs or HTUs? I think very, very exciting times.[00:50:59] swyx: I just wanted to, uh, to maybe illustrate this. I, I'm not the best illustrator, but I, I am a conceptual statistics guy.And y-you know, you cannot just do this. Like this is a dimensionality AB test doesn't do, right? Like, uh, because it doesn't have the, the, the change over time, uh, stochastic nature, uh, and it doesn't have the sort of contextual like... Here's all the context to this point. Um, okay, cool. Um, that's SimGym.You're, you're gonna burn a lot of tokens on this thing. But you're, you're one of the, the only scale platforms in the world that can, uh, that can do this across a huge variety of workloads, right? I'm even curious on a sort of human, uh, research level of like, well, do, does retail behave d-differently from like clothing sales?D-does that behave differently from electronic sales? I, I don't know. I don't know what else you guys... The Kardashian shoppers, do they differ from like people who buy, uh, I don't know, cars and, uh, whatever.[00:51:55] Mikhail Parakhin: Well, very different, and different sensitivities and different modes of, uh, shopping and, and different levels of what's important.Now, to-totally, you can do aggregations at, uh, at a store level. You can do aggregations at a different, uh, category level. I don't know if, uh, you know, for our statisticians among us, I couldn't believe, but we-- recently we're looking at it, and we had to bring back, uh, CRPs, you know, Chinese restaurant process.It's a, like, way of aggregating and, like, naturally grow clustering. So across... Specifically to answer questions that, uh, like you were just posing on how, how if, if buyers behave different categories. And I'm like, “I haven't seen CRP since two thousand and one.” It's[00:52:37] swyx: so What? It's so- What is... No, I haven't, I haven't seen this.No. This is not in my training. Uh,[00:52:44] Mikhail Parakhin: but, but yeah, it, uh, uh, it actually, like the, the-- there was a very popular kind of theory, popular neurips HTML circles in early two thousands, uh, kind of nice. And now, now it has practical applications, uh- Yeah ... that we were resurrecting.[00:53:03] swyx: Yeah, amazing. Uh, I, I can see, I can see how this is like a, uh, a fun job for you where you get to apply all these things.Um, yeah, yeah, so super cool. Super cool. So, okay, so, so anyone who, who knows what CRPs are and has always wanted to use them at work, uh, they should, they should definitely join Shopify. Okay, so w-we have a lot and but I, I'm, I'm being mindful of the time. I, I do wanted to, to sort of cover some other things.Um, I-I'll give you a choice, UCP or Liquid?[00:53:30] Mikhail Parakhin: Liquid. I think, I think on UCP, you know, like UCP is very important for us and, and it just we are-- UCP, we have a structured, uh, discussions, and you can read about them, and we have, uh, blog posts, and we have a big release this week, in fact, like with our catalog.Oh,[00:53:46] swyx: okay.[00:53:46] Mikhail Parakhin: Uh, yeah,[00:53:46] swyx: but- Le-I mean, we, we can, we can discuss the, the, the release briefly because we'll release this after the-- after it's already announced so whatever. There's a catalog that you guys are doing?[00:53:55] Mikhail Parakhin: Yeah. So we are, we are- Okay ... we are bringing in capabilities of a whole, uh, Shopify catalog.Basically, you now you can search for products, you can do lookups by specific ID, you can do bulk lookups when you need to bring m-multiple products. You don't need to know in ad-in advance what you're trying to show or to sell or check out. Like, you can now, you can now have this decided at, at runtime, and this big area for investment for us for both non-personalized and personalized searches, trying to provide basically a win-window into whole universe of products that are being sold everywhere in the world.And Shopify is really not exactly, but almost like a super set of any-anything being sold. Now we are bringing it into UCP and, uh, and, uh, identity linking is another big thing for us, uh, so that you, you can use, uh, like Google or whatever, whatever identity you have, uh, they're minimizing friction.[00:54:56] swyx: Yeah. So[00:54:57] Mikhail Parakhin: yeah, big release for us.But Liquid AI of course we never talk about, and the problem might be more, more aligned with what we d-discussed previously on this chat.[00:55:07] swyx: Sure. The main thing that everyone understands about Liquid is that it is inspired by Worm, and I still don't know why. I'm curious on your explanation. I think you, you, uh, you can make things very approachable.And also I think like what is the potential of like the, the level of efficiency that you get out of Liquid?[00:55:23] Mikhail Parakhin: You- we all familiar with transformer architectures. And, uh, for the longest time, there was a competing architecture, it's called the state space models. So, so Sams, uh, you know, Chris, Chris Reyes, one of the pioneers and, and lots of startups, uh, trying to make those realities.They have, uh, significant benefits being main being, uh, being much faster and, uh, lower footprint and not quadratic in length, you know, sort of, uh, linear in, in, uh, in your context length. But with state space models- They never quite made it. Like they're used-- They have, uh, certain niches when they thrive, their hybrid architectures are useful, but they never quite made it.And liquid neural networks are, you can think of them as a next step, like, uh, sort of, uh, state-space model square. It's non-transformer architecture that's more complicated than sta-state space and really difficult to code if you-- if I'm being honest. But it's, um, very efficient. It's, uh, subline-- sub, uh, quadratic in, in length of your context.Uh, it's very compact way to represent things, and that's a liquid AI company. They... Their goal is to productize it, and very often you have this need, uh, when you need to have long context and small model, and you want to have low latency. Like in general, it's basically on par with transformers, and if you do hybrids with transformers, it's, it's even better.That's why we at Shopify, when we tried multiple and we constantly try multiple models, multiple companies, we found that for small, particularly with low latency applications, when you have low latency and/or if you need longer context lengths, liquid was the best. And so we still use the whole zoo and always like obviously test and use everything, uh, every open source model and, you know, it feels l

Jackson Williams is building large-scale steel sculptures with handmade bending tools, a MIG welder, and a small corner of a shared shop.If you're a welder thinking about getting into metal art, starting small, or building something original without buying a shop full of equipment, this episode will show you what actually matters.• Learn how Jackson builds full-size animal sculptures from half-inch round bar using mostly hand bending and simple jigs • See how he scales reference images on the floor to lay out a framework before skinning a sculpture with rod • Understand why shared shop space can be a smarter move than trying to outfit your own shop from scratch • Hear how posting his work online and saying yes to Fabtech helped create momentum and new opportunities • Take away Jackson's best advice for beginners: start small, play around, and fix anything that is not rightJackson Williams is a steel sculptor based in Asheville, building wildlife and figure sculptures from round bar with a style that emphasizes motion, anatomy, and flow. He developed his craft working alongside his father, sculptor Chris Williams, before carving out his own direction in steel rod sculpture. What makes his work stand out to WELD listeners is how much he's able to create with basic tools, strong fundamentals, and a clear artistic eye.Connect with Jackson Williams:Instagram: @williamssculpture https://www.instagram.com/williamssculpture/ Facebook: https://www.facebook.com/williamssculpture/ TikTok: https://www.tiktok.com/@williamssculpture Website: https://www.williamssculpture.com/ Connect with Beau Wigington:Instagram: @beaudiditweldingDownload the WELD App:iOS: WELD App on the App Store https://foxly.link/m6jqqa Android: WELD App on Google Play https://foxly.link/cYEXjL If this show has helped your career, leaving a 5-star review on Apple Podcasts takes 30 seconds and helps other welders find it.

Civilminister Erik Slottner om AI-revolutionen, om beroendet av amerikanska it-tjänster och om KD efter valet. Lyssna på alla avsnitt i Sveriges Radios app. Erik Slottner (KD) är som civilminister ansvarig för hur regeringen ska hantera den snabba utvecklingen av artificiell intelligens, AI. AI-revolutionen beskrivs ibland som ett av de stora skiftena i mänsklighetens historia. Hur omvälvande tror Erik Slottner att den kommer att bli?”Jag tror att den kommer att bli väldigt stor. Även jag känner mig väldigt liten ibland när vi pratar om AI och de konsekvenser som AI kommer potentiellt att kunna få för oss som människor och våra samhällen”.Nyligen presenterade regeringen sin AI-strategi. Enligt den ska Sverige vara ett av de tio främsta länderna i världen inom AI. Och Sverige ska vara bäst i världen på att använda AI i den offentliga förvaltningen. Regeringen har gett omkring hundra myndigheter i uppdrag att öka användandet av AI under 2026.Kritiken: ”Högriskexperiment”Det här har mött kritik, Akademikerförbundet SSR har kallat det för ett högriskexperiment och menar att rättssäkerheten hotas när AI införs i verksamheter som hanterar känslig information och fattar myndighetsbeslut. Hur ska regeringen säkerställa att människor inte hamnar i kläm när ny teknik ska införas i så här hög fart?”Det där är väldigt svårt att garantera såklart, men vi har ju ett regelverk. Vi har ju väldigt starkt skydd vad det gäller persondata. Vi har starkt integritetsskydd. Det här är gemensamma dataskyddslagstiftningar inom den europeiska unionen. Nu aviserar man att man ska se över en del av detta därför att personskyddslagstiftningen kanske inte går i takt med utvecklingen inom AI. Tekniken går snabbt framåt. Vi kan jobba med kryptering av data som är känslig och ändå få användning av den datan. Men det här måste ske, alltså utvecklingen och användningen måste ske parallellt med utbildningsinsatser. Det här ansvarar till syvende och sist varje myndighet för”, säger Erik Slottner.Borde ni inte skjuta till en ordentlig peng för det här ska vara möjligt att genomföra för de som faktiskt ska göra det.”Det kan man tycka och jag förstår det. Ofta är det så att fackföreningar och myndigheter vill ha mer pengar. Men vi vet också att budgetpåsen är begränsad. Det finns väldigt mycket annat den här regeringen vill göra. Vi har nu ändå gjort den största AI-satsningen någon regering någonsin har gjort”, säger Erik Slottner.It-beroendet av USASvenska myndigheter är beroende av amerikanska it-tjänster för att kunna fungera, allt från molntjänster där data lagras, till e-post och journalsystem. På senare tid har riskerna med ett sådant beroende lyfts. Efter att USA hotade att ta över Grönland förra året började Danmarks regering att fasa ut amerikanska it-tjänster, som Microsoft, på departement. Men Erik Slottner säger att den svenska regeringen inte har några sådana planer.”Nu har ju Danmark en speciell situation, inte minst med det som har hänt med Trump och Grönland. Den diskussionen har accentuerats med anledning av det. Det finns inga sådana beslut om att vi ska klippa banden till amerikanska tech-bolag. Utan vi behöver skapa förutsättningar i Europa för att det ska bli mer attraktivt att investera i molntjänster och utveckla molntjänster i Europa. Där sker det nu ett arbete på EU-nivå med så kallat omnibus-paket som ska göra det mer attraktivt att investera i Europa”, säger Erik Slottner.Under Grönlandskrisen varnade det danska cybersäkerhetsrådet för att USA skulle kunna stänga ner Danmark på en timme om amerikanska molntjänster skulle släckas ner. Vilken är beredskapen i Sverige för om tjänsterna inte skulle gå att använda? ”Jag tror ändå att det scenariot är mycket mycket mycket osannolikt. Vi ska inte skapa nån panikstämning och där människor tror att om en timme eller i morgon kommer vi inte kunna använda min mejlkorg. Vi är inte där. Men med det sagt, ja, det är riskabelt att vara för ensidigt beroende av enskilda länder eller enskilda företag. Därför behöver vi stärka det europeiska oberoendet och suveräniteten inom det digitala området. Kring detta pågår nu ett intensivt arbete. I slutet av maj ska EU-kommissionen komma med förslag på en Data and AI Development Act som ska ge svar på en del av de här frågorna: Hur ska den digitala suveräniteten kunna öka? Det är en mycket viktig fråga för Europa, för vår säkerhet, men också för europeisk ekonomi och konkurrenskraft. Men det ska inte ske genom isolationism och klippa banden till USA”, säger Erik Slottner.KD efter valetDen senaste tiden har Liberalerna och Moderaterna var för sig gjort upp planer med Sverigedemokraterna om framtiden för Tidösamarbetet efter riksdagsvalet i höst. Vad tänker Erik Slottner om att de andra Tidöpartierna gör upp saker om regeringssamarbete utan att Kristdemokraterna är med?”Ebba Busch hade ju sin berömda köttbullelunch redan 2019 med Jimmie Åkesson, där vi tog bort våra röda linjer gentemot Sverigedemokraterna och sade att vi är öppna för samarbete med dem. Det var bilateralt. Sen kom Moderaterna efter, och sen har Liberalerna kommit med där också. Jag välkomnar detta. De får gärna ha bilaterala möten, men den överenskommelse kring politik som de kommer fram till, det står ju inte Tidö bakom, utan det kan bara vara mellan de två respektive partierna. Sen ska det förhandlas efter valet”, säger Erik Slottner.Gäst: Erik Slottner (KD), civilminister Programledare: Johar BendjelloulKommentar: Evelina GalliProducent: Maja Lagercrantz Tekniker: Christian BarterIntervjun spelades in den 10 april 2026.

Kære lyttere. Der findes gæster, man glæder sig til. Og så findes der gæster, man næsten ikke tør håbe på. Ventetiden er endelig forbi. Episoden med Ghita Nørby er klar! Vi taler om livet, kunsten, sproget og bevæger os fra Matador, Dirch, Mig og Charly og hen til Dansen med Regitze + alt det du selv får lov til at opdage. Det blev nørdet, varmt, ærligt, overraskende & sjovt. Indimellem helt stille på den der måde, hvor man godt ved, at noget vigtigt lige blev sagt. Vi håber, I vil lytte med. Episoden ligger klar nu der, hvor du finder dine podcasts. Kh Thomas & Danni

Påskspecial står på schemat och vi gästas av nära vänner. Tone Schunnesson om när hon slog Christopher på käften. Christopher delar med sig av sin pinsammaste jag sket ner mig-historia och Ragge river taket när Hannas alla historier ska synas. Lyssna på alla avsnitt i Sveriges Radios app. Programledare: Hanna Hellquist & Christopher Garplind

A version of this essay has been published by firstpost.com at https://www.firstpost.com/opinion/shadow-warrior-drones-are-the-new-tanks-time-for-india-to-catch-up-13998019.htmlThe most important lesson (of many) from Gulf War 3 may have been foreshadowed by the Ukraine War and other conflicts: that a combination of a step-change in warfare (military strategy) and disruptive innovation (business strategy) could rewrite the rules. If so, we may need to rethink the value of much expensive hardware. Moreover, nations such as India may need to seriously revamp their arms procurement: to small, cheap, local maybe?The most disturbing aspect of this scenario is that it reduces the human factor, and human control, over warfare. It leads to the specter of robot warfare, of Skynet, of 2001: A Space Odyssey, where autonomous intelligences may take rational decisions that have grave consequences for humans, inflicting collateral damage on innocent bystanders in ways that nobody quite understands. We need a real-life version of Isaac Asimov's “Three Laws of Robotics”. But then humans too inflict unthinking collateral damage..Step-change in warfare, and disruptive innovationThere have been numerous instances where a settled and standardized war tactic was suddenly overturned by a new invention, rendering old military assets impotent. One or two examples will suffice: one was the eclipse of heavy cavalry after the invention of massed archers using longbow volleys to mow them down with thousands of synchronized arrows raining down, also inducing panic in their horses in mid-charge.Another example is how battle tanks overwhelmed the previous model of trench warfare. (Ironically, in turn, tanks are now being rendered sitting ducks by drones.)In both cases, long-held assumptions had to be rewritten practically overnight, and entirely new mechanisms had to be put in place. It is a good question (on which reasonable people may differ) as to whether the arrival of drone-and-missile-based warfare is rendering air power, including fighters, bombers and aircraft carriers, essentially obsolescent.Clayton Christensen articulated the theory of disruptive innovation in business, where an entrenched incumbent can be overthrown in short order by an insurgent attacking them from an unexpected direction, often based on lower-cost options. One example is that of Kodak and the film-camera business. Cheap and convenient digital photography dislocated Kodak et al practically overnight.I personally experienced this disruption in the 1990s when I had a key role in operating system strategy for Sun Microsystems, the runaway leader in engineering workstations and servers, which used the Unix operating system. Despite our best efforts, Microsoft+Intel coming in from the low end (as Windows systems became more capable) rapidly captured the key resource, which is third-party software vendors. This caused end users to desert in droves.There were other reasons, too: internecine warfare among firms using Unix, such as IBM, HP, Sun, AT&T, Toshiba, et al. While they bickered, Windows systems became more powerful. Lesson: the ecosystem has to be managed carefully, including supply chains.Putting these three together (step-change, disruptive innovation, and the ground realities of the Gulf War 3) one can speculate that future military doctrine will be vastly different. Here is Iran's military doctrine, for reference, from the substack NotesonGeopolitics (Disclaimer: I am neither endorsing it or criticizing it, just offering it as an example).The US is adjusting to this reality. There is a book titled “Project Maven”, based on 200+ interviews chronicling the US military's shift to AI-driven warfare, starting with a 2017 Pentagon project to automate drone footage analysis amid overwhelming data volumes.Project Maven evolved from error-prone early tools (such as misidentifying school buses as threats) to supporting autonomous systems like Goalkeeper drones and Whiplash naval units, now used in conflicts from Ukraine to the Caribbean by 25,000 personnel across 32 companies.Speaking of disruptive innovation, it is ironic to see the US reverse-engineering Iranian Shahed drones, and the Russians doing the same to Ukrainian drones: incumbents learning from insurgents.This is only the beginning, of course. There is a nightmare scenario: murmurating, autonomous drone swarms with a hive mind. A flock of starlings flying in perfect synchrony is a thing of beauty: they do not collide with each other, the entire swarm changes direction instantaneously, and there is emergent intelligence in the swarm, much greater than the intelligence of the individual bird. The same is true of beehives and ant colonies, too.A company called ShieldAI in fact has a product named Hivemind that does precisely this.Imagine a murmurating drone swarm of 1,000 or even 10,000: and since they cost so little make, this is not unrealistic. The enemy may shoot down 90% of them, but the 10% that gets through, especially if they are kamikaze drones fitted with explosives, can cause real damage. There is the old joke about quantity: “What do you do when you invade China? First day, you take 10,000 prisoners. Second day, you take 100,000 prisoners. Third day, you surrender!”But we don't have to go that far: just take two instances where inexpensive drones were able to penetrate the defenses of heavily secured military airports. The first was in Russia in June 2025. Using 117 low-cost drones, Ukrainians struck several airbases at once. There is video footage of FPV drones landing on Tu-95 bombers, destroying them. These are strategic long-range nuclear bombers from the Cold War era, and will be difficult to replace.And then, just last month: at Barksdale Air Force Base in the US, where B-52 nuclear bombers are deployed, there were repeated drone swarm overflights (of 12-15 drones) between March 9th and March 15th, 2026. They couldn't be jammed, and displayed “non-commercial signal characteristics”, although they did not actually attack the planes. Reconnaissance, it must be assumed. Superpower militaries are unable to contain them.Electronic warfare like jamming may be ineffective anyway as swarms self-repair. But it is true that there are air defense weapons that can shoot down the majority of drones. There are interceptors (but they are much more expensive than the drones themselves). Then new Directed Energy Weapons (including both lasers and high-powered microwaves) are in development. Rail guns, I understand, are overkill for them.Where is India in this arms race?India finds itself left behind in this transition, and remains committed to legacy platforms such as tanks, fighters, and other imported systems. It is true that there were battlefield successes in Operation Sindoor, where X-25 drones (towed on a 100 meter optical cable) emitted the radar signatures of Rafale fighter jets, thus drawing enemy missiles to themselves, without harming the planes. But these were Israeli products; also British-origin Banshee drones were used for spoofing Su-31 and Mig-29 signatures..Indigenous drone efforts lag China by 3-5 years in scale, AI integration, and mass production; reliance on Chinese components persists despite bans. It does not have to be this way: India should create Production Linked Incentives for drones and missiles, and harness Machine Learning and Artificial Intelligence at scale.India needs to promote this as a cottage industry, so that many individuals will get involved, as in the following post by a Ukrainian drone-maker, with a hashtag #MadebyHousewives. That country produces as many as 4.5 million cheap drones a year, often using 3d printing.While Ukraine and Iran improvise hive-mind swarms under fire, India's northeast and border regions face asymmetric threats from low-cost systems. The recent mercenary scandal in the Northeast illustrates the peril. Mercenaries, the Northeast and a new Christian enclave?The March 2026 arrests by India's National Investigation Agency (NIA) expose how this drone proliferation directly endangers the Seven Sisters. Six Ukrainians and American mercenary Matthew Aaron Van Dyke were detained across Indian airports. They had repeatedly crossed from restricted Mizoram into Myanmar since 2024, training ethnic insurgent groups in drone assembly, operation, jamming, and electronic warfare.They smuggled European drone consignments through India for insurgent networks, some linked to proscribed Indian groups operating in the northeast. This is no abstract threat: drones enable precision strikes on security forces, surveillance of remote terrain, and supply drops. These capabilities could ignite or sustain insurgencies in India's volatile borderlands.In the background is former Bangladesh Prime Minister Sheikh Hasina's explosive 2024 warning. Hasina alleged a “white man's” conspiracy to carve out a new “Christian nation” (akin to East Timor or South Sudan) from Bangladesh's Chittagong Hill Tracts, Myanmar's Rakhine and Chin regions, and India's Northeast. She cited foreign eyes on the Bay of Bengal and ethnic fault lines.Hasina's claim was dismissed as paranoia then; today, Ukrainian-American actors arming Myanmar's rebel groups lend credence to a broader destabilization playbook. A hive-mind-enabled drone campaign could empower separatists and create a Christian-majority enclave, exploiting Christian tribal demographics and porous borders. This is hybrid warfare at its most insidious: mercenaries as force multipliers for great-power proxies.If these insurgents can leverage drone swarms to close the Siliguri Corridor or target regional infrastructure, they can create a fait accompli on the ground for India.ConclusionThe drone-missile age demands urgent adaptation. Nations must invest in AI swarm doctrine, resilient EW, decentralized deployment, and indigenous mass production ecosystems. For India, the wake-up call is clear: clinging to legacy investments while insurgents import hive-mind precursors risks not just military irrelevance but territorial integrity. The Tu-95 pyres and B-52 overflights are warnings. The northeast drone pipeline is a direct threat. Warfare has changed; those who fail to swarm will be overrun.Here is the AI-generated audio podcast about this essay:1570 words, Apr 3, 2026 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit rajeevsrinivasan.substack.com/subscribe

Send us Fan MailRob "Z-Man" Zettel shares what it was like to fly the MiG-23 Flogger with the "Red Eagles" with plenty of good stories throughout!We also chat about his book "American MiG Pilot" which you can pick up via the link below.Pick up Z-Man's book - https://robzettel.com/*Pick up one of our patches -  https://ebay.us/m/B0gs3iHelp to keep the channel going:         PATREON - https://www.patreon.com/aircrewinterviewDONATE - http://www.aircrewinterview.tv/donate/* Pick up some AI merch - https://www.teepublic.com/user/aircrew-interview  Follow us: https://www.aircrewinterview.tv/https://www.instagram.com/aircrew_interviewhttps://www.facebook.com/aircrewinterviewhttps://www.twitter.com/aircrewtvSupport the show

La Rvfleuze débarque avec toute son équipe : Favé, MIG, le duo LA KADRILLA, Saamou et SAFOI2 pour la première émission dédiée à son nouvel album "Numéro d'écrou" !

Cezary Tomczyk o bezpieczeństwie Polski, budowie systemów, o MIG-ach dla Ukrainy, F-35, kontrowersyjnej wizycie prezydenta Polski na Węgrzech, planach MON i SAFE 0 proc.

Send us Fan MailFormer USAF F-4 Phantom and F-5 aggressor pilot, Rob "Z-Man" Zettel shares how he came to fly the MiG-21 in the very secret programme for the 4477th Test and Evaluation Squadron aka the "Red Eagles" which includes some great insights into flying the aircraft and flying DACT against the USAF and USN!Pick up Z-Man's book - https://robzettel.com/*Pick up one of our patches -  https://ebay.us/m/B0gs3iPart 1 - 22 MarchPart 2 - 29 MarchHelp to keep the channel going:         PATREON - https://www.patreon.com/aircrewinterviewDONATE - http://www.aircrewinterview.tv/donate/* Pick up some AI merch - https://www.teepublic.com/user/aircrew-interview  Follow us: https://www.aircrewinterview.tv/https://www.instagram.com/aircrew_interviewhttps://www.facebook.com/aircrewinterviewhttps://www.twitter.com/aircrewtvSupport the show

In this episode, host Beau Wigington breaks down 27 different welding processes and ranks them by utility, accessibility, and overall cool factor. From shop staples like MIG, TIG, stick, and flux core to niche processes like atomic hydrogen, electron beam, and thermite welding, Beau gives his honest take on which methods are the most practical, which are the most interesting, and which ones are just plain fun to talk about.Whether you're new to welding or already deep in the trade, this episode is a great overview of how many different paths exist in the welding world, and why some processes earn a permanent place in the conversation.Save 20% On Related American Welding Program Courses With WELD20Use code WELD20 at checkout for eligible courses - https://foxly.link/9T3dtc Connect with Beau WigingtonInstagram: @beaudiditwelding — https://www.instagram.com/beaudiditwelding LinkedIn: https://www.linkedin.com/in/beauwigington E-mail: beauw@weld.comWatch The Video Version Of The Podcast - https://youtu.be/ATdFcSDQ8UM

IRON EAGLE (1986) - Couch Potato Theater: Fandom Podcast Network Classics Listen: Couch Potato Theater Audio Podcast Link: https://fpnet.podbean.com/category/couch-potato-theater Welcome to Couch Potato Theater: 'Fandom Podcast Network Classics', where we celebrate our favorite movies on the Fandom Podcast Network!  We're re-releasing IRON EAGLE (1986), Couch Potato Theater. Originally recorded in 2019. Your Couch Potato Theater co-hosts and Fandom Podcast Network founders Kevin & Kyle are joined by guests Amy Nelson & Hayley Stoddart, our co-hosts from our Union Federation Star Trek & The Orville podcast. Sit back and relax on the couch and enjoy this special re-release presentation of IRON EAGLE (1986) - Couch Potato Theater. Iron Eagle is a 1986 action film directed by Sidney J. Furie who co-wrote the screenplay with Kevin Alyn Elders, and starring Jason Gedrick and Louis Gossett Jr.  Plot: When Doug's father, an Air Force Pilot, is shot down by MiGs belonging to a radical Middle Eastern state, no one seems able to get him out. Doug finds Chappy, an Air Force Colonel who is intrigued by the idea of sending in two fighters piloted by himself and Doug to rescue Doug's father after bombing the MiG base. Their only problems: Borrowing two fighters, getting them from California to the Mediteranean without anyone noticing, and Doug's inability to hit anything unless he has music playing. Then come the minor problems of the state's air defenses. Fandom Podcast Network Contact Information - - Fandom Podcast Network YouTube Channel:  https://www.youtube.com/c/FandomPodcastNetwork - Master feed for all FPNet Audio Podcasts: http://fpnet.podbean.com/ - Couch Potato Theater Audio Podcast Master Feed: https://fpnet.podbean.com/category/couch-potato-theater - Facebook: https://www.facebook.com/Fandompodcastnetwork - Email: fandompodcastnetwork@gmail.com - Instagram: https://www.instagram.com/fandompodcastnetwork/ - X: @fanpodnetwork / https://twitter.com/fanpodnetwork -Bluesky: @fanpodnetwork / https://bsky.app/profile/fanpodnetwork.bsky.social Host & Guest Contact Info: - Kevin Reitzel on X, Instagram, Threads, Discord & Letterboxd: @spartan_phoenix / Bluesky: @spartanphoenix - Kyle Wagner on X: @AKyleW / Instagram & Threads: @Akylefandom / @akyleW on Discord / @Ksport16: Letterboxd / Bluesky: @akylew Guests: - Amy Nelson on X: @MissAmyNelson / Instagram: @amynelson522 /  Blue Sky: @CounselorAmy - Hayley Stoddart on Instagram & Bluesky: @trekkie01D #IronEagle #CouchPotatoTheater #FandomPodcastNetwork #FandomPodcastNetworkClassics #JasonGedrick #LouisGossettJr  #IronEagle1986 #IronEagleMovie #CPT #FPNet #FPN #SidneyJFurie #DavidSuchet  #ShawneeSmith  #MeloraHardin  #LarryBScott  #LanceLeGault  #TimThomerson  #CarolineLagerfelt  #RobertJayne  #JerryLevine  #RobbieRist  #MichaelBowen  #KevinAlynElders #1986Movies #KevinReitzel #KyleWagner #AmyNelson #HayleyStoddart    

It moved towards Antistrophe, Caoimhe, and Nicky through the dark as something other than itself. A creature of guile and hunger, whose taste for life is well developed and whose limbs are the limbs of others. Meanwhile, amidst the revelers of the High Masque, the moonlit wing's adventurers mix and mingle. Will they try to puzzle their way through the rhyming door, or sate themselves on delicacies and dances instead of dungeoneering… This week on Perpetua: The Castle Eschatonica 05 Perpetua Guide [Community Addendum Part 03] What's up every-freakin-body. It's THEUNFORGIVENIII and I decided to pick up on Nei's slack. Maybe he'll see what a good job I'm doing and come back to try to one up me. Then the real rivalry will begin… Anyway, it's boss fight time. I made a few updates to Nei's format. I KNOW that he says he doesn't wanna get some specific spoilers in these enemy rundowns but I think that's pretty fuggin lazy. Maybe you can learn a few things from a real gamer, Nei. (bcuz i KNOW you're secretly reading along) Strange Hornet [NMSH] LEVEL: 10 RANK: SOLDIER TYPE: BRUTE TRAITS: CORPSE, PUPPETTED, UNDEAD STATS: DEX 8, INS 6, MIG 10, WLP 8 DEF: 8  MAGDEF: 6 HP: 70 MP: 45 INITIATIVE: 7 ATTACKS Buzzing Bash: Melee, [MIG + MIG], [HR + 10] PHYSICAL DAMAGE Stinger Shot: Ranged, [DEX + MIG], [HR + 5] PHYSICAL DAMAGE SPECIAL ABILITIES Brute: +1 to all accuracy and magical accuracy rolls Just a Puppet: "When the strange Hornet is reduced to 0 Hit Points for the first time, it is instead reduced to exactly 1 Hit Point and Malathornia, Wicked Weaver is revealed." ELEMENTAL INFO: Vulnerable to Fire and Light IN-GAME DESCRIPTION: It's moving weird… EXPERT INFO: If you think "we're really kicking this guy's ass, this must be a fakeout," then you're at least a class B Gamer. Because the second you beat this guy into the ground, the real boss shows up! PROTIP: REMEMBER: BECAUSE THIS GUY COUNTS AS UNDEAD, YOU CAN HURT HIM WITH HEALING SPELLS! (BUT BE CAREFUL, BECAUSE ALL SPELLS ONLY HEAL HALF DAMAGE INSIDE OF REDOLENCIA CELESTIAL ECHOES)   Malathornia, Wicked Weaver [NMML] LEVEL: 10 RANK: CHAMPION (3) TYPE: SABOTEUR TRAITS: CONNIVING, MANIPULATIVE, CRAVEN, AMBITIOUS (SOUNDS LIKE MY STEP-DAD ROFL)  STATS: DEX 8, INS 8, MIG 8, WLP 8 (BORING) DEF: 10 MAGDEF: 9 HP: 180 MP: 100 INITIATIVE: 11   ATTACKS Thieving Webs: Ranged, [DEX + WLP] + 4, [HR + 5] PHYSICAL DAMAGE - MULTI 2 - EACH TARGET HIT BY THIS ATTACK LOSES 1 IP Enervating Claws: Melee, [DEX + WLP] +4, [HR + 5] DARK DAMAGE - EACH TARGET HIT BY THIS ATTACK IS WEAKENED. TARGETS MAGICAL DEFENSE.   SPECIAL ABILITIES Catch Me If You Can: Malathornia enters the conflict accompanied by a Pursuit Clock with 10 sections. Enemies cannot see Malathornia unless half or more of the Pursuit Clock's sections are filled. Back to the Shadows: Malathornia skitters back into the shadows of the Ruined Hive. Remove up to 2 marks from the pursuit clock. Malathornia's Marionette: Malathornia spends 20 MP and chooses a target suffering from Weakened. Malathornia's webs puppet the target, forcing them to immediately perform a free attack with an equipped weapon or basic attack against a target chosen by this NPC.   ELEMENTAL INFO: Resistant to Physical (YIKES) and Dark. Vulnerable to Light.   IN-GAME DESCRIPTION: Ruiner of the Old Hive. Master of the Shadows.   EXPERT INFO: This is the only "real" boss you can fight in this first part of the dungeon, but personally, I think he's a chump. Just use Caoimhe's light attacks to demolish this freak. (if you didn't Give Caoimhe light spells yet, then that's on you!)   PROTIP: REMEMBER THAT YOU CAN USE ITEMS FOR EXTRA HEALING IF YOU NEED IT (LIKE IF YOU'RE A NOOB).

In this episode of The Box of Oddities, Kat and Jethro explore a chilling moment of Cold War history and descend into the strange world of underground conspiracy theories. First, American soldiers on a Korean War patrol stumble upon a crashed MiG-15 fighter jet frozen into a mountainside—its young pilot eerily preserved in ice, as if time itself simply stopped. Then the conversation tunnels into bizarre modern myths: secret Walmart tunnel networks, the alleged alien-linked Dulce Base beneath New Mexico, hidden passageways under Los Angeles, and mysterious facilities buried deep beneath Antarctic ice. What happens when real history, classified military activity, and human curiosity collide? Expect weird facts, bizarre history, and strange stories that blur the line between documented events and the conspiracies they inspire. If you love odd discoveries, Cold War mysteries, and underground legends, this episode is packed with curiosity-fueling intrigue. Learn more about your ad choices. Visit megaphone.fm/adchoices

HEADLINE: Taiwan's Stance on Nuclear Weapons ProliferationGUEST: Grant Newsham Taiwancurrently lacks the public or political appetite for a nuclear weapons program, despite having one shut down by the United States in the 1980s. While neighboring nations like South Koreaand Japan show increasing interest in nuclear capabilities, Taiwan does not openly discuss this as a defense strategy. Experts caution that while nuclear weapons can feel "comforting," they are not a "fail-safe" because they could trigger overwhelming retaliation from the mainland. (6)APRIL 1953 MIG-15 CAPTURED IN KOREA

In this episode of The Headache Doctor Podcast, Dr. Jono Taves explains why having a clear migraine treatment plan is one of the most important factors in long-term healing.Too often, headache and migraine sufferers are given medication without a clear explanation of why their symptoms are happening or how to move forward. Dr. Taves shares a personal story from his newborn son's recent hospital stay to illustrate how powerful it is when a provider explains the “why” and lays out a clear direction.You'll learn:Why uncertainty makes migraines feel worseThe difference between symptom suppression and root-cause careWhy time can work for you instead of against youHow the Three-Spoke framework identifies the source of pain, barriers to healing, and systemic health contributorsWhy medication alone often fails to solve chronic headachesIf you've ever felt stuck, confused, or dismissed in your migraine care, this episode will help you understand why having a plan changes everything.Novera: Headache Center

Nick and Jeni Clift are the owners & Directors of DWM Solutions, now merged with Milan Industries Group.  They have been working together in their own businesses for close to 25 years.Nick is Director of MIG, and holds the role of Visionary.Jeni is Head of People & Culture at MIG. She also has a consultancy business, Tenassia, working with her clients as an EOS Implementer and providing Business & Leadership Coaching.DWM Solutions opened for business in February 2002. We provide proactive IT support services for Local Government, Water Authorities, Education and Health entities as well as small to medium Commercial organisations. In a nutshell, we think about your IT so you don't have to!Our clients are located across Victoria, we support them from our offices in Melbourne, Bendigo and Echuca, and in January 2017 we relocated our Geelong office to Torquay.  We currently employ 16 staff.Prior to founding DWM Solutions, Nick held various roles within the computer and information technology industry. These included Director and General Manager of TriTech Computer Services; and Engineer, Service Manager and National Technical Services Manager over a 13-year career with Unisys.  Nick holds Certificate of Technology in Electronics and Certificate of Technology in Computer Servicing from RMIT.  These, coupled with his extensive industry and product certifications, highlights a wealth of knowledge and skills. More than 30 years of experience in the computer industry has given Nick a sound understanding of the important role technology plays in business. His ability to keep abreast of the ever-changing pace of information technology is second to none.Jeni's background is in Human Resources & Administration, she has worked with many of Australia's best known brands, including Morgan & Banks, P&O, KPMG, NAB, Unisys and Phillips. Jeni is a Professional EOS Implementer and works as a Business Coach specialising in Leadership and Personal Development.  Jeni is a regular speaker at IT industry events and internationally, sharing her experiences in running a family business and managing the “people” side of a business.

PREVIEW FOR LATER TODAYHEADLINE: Beijing's Global Strategy to Weaken America25 WORD SUMMARY: Bill Gertz warns that China is covertly arming Russia and supporting US enemies as part of a broader strategy to displace and destroy the United States.GUEST: Bill Gertz, The Washington TimesAPRIL 1953 MIG-15

This episode includes discussion of animal injury and illness, including descriptions of wounds and death. A mystery (and the need for a little spending money) has sent the crew of the Little Snail up into the hills of Spillaway Peaks. In between attending to their escortee, the locally famous photographer Waylon, Veile, Nicky, Jonathan, and Elena encounter the edges of a strange curse. What has happened to the Oxen of the Peaks? Can it be reversed? And what might it mean for the Perpetuan Cycle… This week on Perpetua: A PIcture of the Hills 04 Perpetua Guide [In Progress v.058] NPCs & Monsters [PNMS] Waylon, Local Photographer [NMWY] Traits: Stubborn, Experienced, Prickly, Soft-Hearted Stats: ???  Attacks: ??? Special Abilities: ???  In-Game Description: Spillaway Peaks local photographer has been serving the community for hundreds of years. His hard shell covers a soft interior. To be honest, I haven't actually seen Waylon's "soft-heart" yet, but maybe that'll come in time.  Starter Tip: If you fail to convince him to make a detour while you grind or do other side quests, do NOT let him wander away! He will immediately start taking damage once you're on a different screen. Brown Flegg [NMBF] Typical Traits: Mischievous, Stubborn, Direct, Family Oriented  Stats: DEX 8, INS 8, MIG 8, WLP 8 Attacks: Flegg Strike, Infuriate, Flegg Gale Special Abilities: Stoneshell In-Game Description: A living egg. It comes up to your shins. Hey, why are these ones brown!? A leveled up version of the classic Flegg. They're level 10, so expect a higher HP pool. Their Flegg Gale also gives them a little extra "oomph." Be careful if you have a status that weakens you to Air damage! Starter Tip: Their resistances and vulnerabilities are different than the base Flegg. These ones are strong against both earth and fire damage, but are weak to poison! Sentishell [NMSS] Traits: Justice-Seeking, Protective, Noble Stats: DEX 8, INS 8, MIG 8, WLP 8  Attacks: Hilt Bash, Holy Slash Special Abilities: Holy Aegis, Stoneshell, Threaten In-Game Description: Extra-large, light-green Flegg with brown splotches. Wears shining platemail armor and helm, visor raises so that you can see his brave expression. Wields a long sword and Kite shield commensurate to his size. A Paladin-type Flegg!? Yup, your eyes aren't deceiving you. This little guy has pretty standard stats, but lots of defensive moves to help keep him and his crew safe from incoming damage. I wonder if we could recruit him to OUR side.  Starter Tip: Both his Holy Aegis and Threaten skills can be canceled by hitting him with either Dark or Lightning damage! So prioritize those! Hosted by Austin Walker (austinwalker.bsky.social) Featuring Ali Acampora (ali-online.bsky.social), Art Martinez-Tebbel (amtebbel.bsky.social), Jack de Quidt (notquitereal.bsky.social), and Andrew Lee Swan (swandre3000.bsky.social) Produced by Ali Acampora Music by Jack de Quidt (available on bandcamp) Cover Art by Ben McEntee (https://linktr.ee/benmce.art) With thanks to Amelia Renee, Arthur B., Aster Maragos, Bill Kaszubski, Cassie Jones, Clark, DB, Daniel Laloggia, Diana Crowley, Edwin Adelsberger, Emrys, Greg Cobb, Ian O'Dea, Ian Urbina, Irina A., Jack Shirai, Jake Strang, Katie Diekhaus, Ken George, Konisforce, Kristina Harris Esq, L Tantivy, Lawson Coleman, Mark Conner, Mike & Ruby, Muna A, Nat Knight, Olive Perry, Quinn Pollock, Robert Lasica, Shawn Drape, Shawn Hall, Summer Rose, TeganEden, Thomas Whitney, Voi, chocoube, deepFlaw, fen, & weakmint This episode was made with support from listeners like you! To support us, you can go to friendsatthetable.cash.

Met vandaag: Hoe gaat het in de formatie? | James Kennedy over de nationale discussie in de VS na de tweede dodelijke schietpartij in Minneapolis | Wat is de impact van de moord op leraar Samuel Paty ruim vijf jaar na dato? | MiG-killer F16 naar het museum, piloot Peter 'Wobble' Tankink haalt herinneringen op | Regisseur Dan Geesin en actrice Jasmine Sendar over film 'Een mislukt eerbetoon aan moederliefde' | Presentatie: Mieke van der Weij

ELON MUSK AND THE GOLDEN DOME DEFENSE PROPOSAL Colleague Henry Sokolski. Sokolski evaluates Elon Musk's proposal to create a "Golden Dome" missile defense system for the US. While the concept involves space-based sensors, Sokolski notes concerns regarding monopoly power, the reliance on a single contractor for national security, and the undefined costs of ground-based interceptors. NUMBER 101953 captured Mig-15

A sudden confrontation! Having 'sniffed out' a lead, Antistrophe, Brontë, and Caoimhe have dug their way towards the truth. That truth rests in the underground archive of the Hexcloaks' regional headquarters in Cenn, City of Iron Chains. But such a basement does not go unguarded. To arms, Team ABC! This week on Perpetua: In Too Deep 03  Perpetua Guide [In Progress v.055] NPCs & Monsters [PNMS] Hortensius, Venomous Hexcloak [NMHR] Traits: Joyful, Experimental, Cruel Stats: DEX 6, INS 10, MIG 6, WLP 10 Attacks: Toxic Whip, Poison Cloud Special Abilities: Heal In-Game Description: A misanthropic hexcloak with a mastery of toxins, venoms, and other poisons. Hortensius may not seem like the most dangerous of the Cenn Hexcloak Trio, but his mastery of poisons means that he can really wear you down (or set you up for another of the trio to knock you out.) Unsurprisingly, he resists poison damage. Starter Tip: Poison Cloud can hit everyone, and it always hits. Get ready to use some tonics!  Maxi, Earthen Hexcloak [NMMX] Traits: Tough, Direct, Snobbish Stats: DEX 10, INS 6, MIG 12, WLP 6 Attacks: Stone Maul Special Abilities: Status Immunity, Stoneshield In-Game Description: A Hexcloak soldier who combines expertise of earthen enchantment with finely honed martial prowess. Maxi is proof that sometimes all you need is a big stick. She doesn't have special attacks or active abilities, just a collection of strong defensive passives and a really high Might (which she tends to keep high because of her Status Immunity ability).  Starter Tip: She resists both earth and, more importantly, physical damage. Spell damage is your best bet here! Mercurion, Voltaic Hexcloak [NMMR] Traits: Laconic, Rude, Mercurial Stats: DEX 10, INS 10, MIG 6, WLP 6 Attacks: Electrified Dagger, Hexipistol, Fulgur Special Abilities: Flying (Bugged?) In-Game Description: Impudent in speech. Electric in action. Mercurion seems to be the leader of the Cenn Hexcloak Trio, and for good reason. They can dish out big damage QUICK with their Fulgur ability (and it also has a low chance of making you dazed). Try to knock them down even quicker, or else Hortensius' heal will make them a real pain in your behind. Starter Tip: The game says they're flying, and they have a hovering animation, but some people have reported that Mercurion isn't actually flying in their boss fight. So don't worry if it seems broken, it's just a bug!