Podcasts about Superhuman

Hoe goed is de Nederlandse zorg voorbereid op oorlog, cyberaanvallen of andere grote crises? In deel 2 van de vierdelige serie ‘zorg in tijden van crisis’ onderzoekt BNR Beter welke medische kennis nodig is om de zorg draaiende te houden als de samenleving ontwricht raakt. Want oorlogszorg vraagt om andere vaardigheden, andere systemen en een andere mentale voorbereiding dan de reguliere zorg. In deze aflevering van BNR Beter spreekt Nina van den Dungen met drie experts die dagelijks bezig zijn met medische weerbaarheid in crisissituaties. Te gast zijn Edith Willigendael, vaatchirurg en Kolonel-arts bij Defensie, Ruud Wong Chung, fysiotherapeut en onderwijskundig onderzoeker, en Fieke Bruggeman-Everts, sociaal wetenschapper en beleidsadviseur bij ARQ Nationaal Psychotrauma Centrum. Edith Willigendael vertelt hoe moderne oorlogsvoering de medische zorg fundamenteel verandert. Door drones ontstaan andere soorten verwondingen dan in eerdere conflicten, terwijl mobiele ziekenhuizen en medici zelf steeds vaker doelwit zijn geworden. Ze beschrijft hoe Oekraïne noodgedwongen werkt met kleine, ondergrondse zorgposten dicht bij het front, en waarom Nederland lessen moet trekken uit landen als Oekraïne en Polen als het gaat om cyberveiligheid, logistiek en paraatheid. Ruud Wong Chung vertelt over het internationale project Netherlands for Superhumans, waarbij Oekraïense multidisciplinaire revalidatieteams zes weken lang in Nederland worden opgeleid. Dat project is onderdeel van een bredere Nederlands-Oekraïense samenwerking om de revalidatiezorg in Oekraïne op te schalen voor oorlogsslachtoffers met amputaties, hersenletsel en zwaar trauma. Nederlandse experts uit onder meer De Hoogstraat, UMC Utrecht en ARQ trainen honderden Oekraïense zorgverleners. Tegelijkertijd leren Nederlandse medici juist van de flexibiliteit en creativiteit waarmee Oekraïense ziekenhuizen onder extreme druk moeten functioneren. Het Project Netherlands for Superhumans wordt gefinancierd door RVO, binnen het Ukraine Partnership Facility (UPF). Betrokken partners zijn Stichting “Netherlands for Ukraine Foundation” (NL4UA), Stichting “Healthcare4Ukraine” en Charitable Fund “Superhumans”. Fieke Bruggeman-Everts legt uit waarom mentale weerbaarheid minstens zo belangrijk is als medische kennis. Op basis van de coronacrisis ontwikkelde ARQ samen met de zorgsector een landelijke richtlijn voor psychosociale ondersteuning van zorgprofessionals. Daarin staan aanbevelingen over peer support, teamcultuur en stressbegeleiding voor mensen in hoog-risicoberoepen zoals zorg, defensie en ambulancezorg. Volgens Bruggeman-Everts begint goede crisiszorg bij een veilige werkomgeving waarin collega’s elkaar ondersteunen en problemen vroegtijdig bespreekbaar zijn. Over deze podcast BNR Beter is het wekelijkse programma van BNR Nieuwsradio over een toekomstbestendige zorgsector. Elke week bespreekt presentator Nina van den Dungen met zorgprofessionals, ondernemers en beleidsmakers hoe de Nederlandse zorg met technologie, innovatie, regelgeving en wetenschap beter kan worden. BNR Beter is elke maandag om 15:30 op de radio te beluisteren bij BNR Nieuwsradio, en vanaf dat moment ook als podcast via deze feed. Over de makers Nina van den Dungen (1987) is freelance journalist en als radio- en podcastpresentator al ruim 15 jaar verbonden aan BNR. Zo is ze regelmatig te horen als presentator van de nieuwsprogramma's in de ochtend- en avondspits en daarnaast presenteert ze wekelijks de beleggingspodcast Doorgelicht en BNR Beter over de zorgsector. Stijn Goossens (1996) is de redacteur van BNR Beter en plaatsvervangend presentator. Bij BNR houdt Stijn zich bezig met onderwerpen over tech, wetenschap en innovatie. Hij presenteert ook de podcast Op de zaak en test elke vrijdag een nieuw techproduct in de Ochtendspits op BNR. Hiervoor was Stijn werkzaam voor NTR Wetenschap en techplatform Bright.See omnystudio.com/listener for privacy information.

The Pope called for AI to be "disarmed" — then gave Anthropic a seat on the dais. Nitasha Tiku (The Washington Post) unpacks what the Vatican's landmark intervention means for Silicon Valley. Then, get off Nextdoor, Kyle Chayka (The New Yorker) says hyperlocal publications are in vogue and a respite from algorithmic feeds. And finally, an update on last weekend’s Enhanced Games in Las Vegas. Journalist Chris Gayomali, host of the podcast SuperHuman, persevered through the 95-degree heat and d-list Gen Z influencers to witness one world record that almost didn’t happen. Additional Reading: Can AI be a ‘child of God’? Inside Anthropic’s meeting with Christian leaders. | The Washington Post Pope Leo Warns of Risks From A.I. in 42,300-Word Encyclical | The New York Times Your Friendly Neighborhood Newsletter | The New Yorker SuperHuman Podcast | Vegas Download SAILY in your app store and use our code techstuff at checkout to get an exclusive 15% off your first purchase! For further details go to https://saily.com/techstuffSee omnystudio.com/listener for privacy information.

Is inbox zero actually making you more productive… or just more reactive?In this solo episode of Time to Reset, Penny Zenker challenges one of the biggest productivity myths of the modern workplace: the obsession with clearing your inbox.Penny breaks down why email has become one of the greatest drains on our time, energy, and focus — and why using your inbox to drive your day keeps you stuck in reaction mode instead of focused on what truly matters.She also shares:Why “inbox zero” is an outdated strategyHow AI and modern tools are changing productivityThe mindset shift that creates more clarity and controlWhy your email should never be your task listSimple ways to reduce overwhelm and regain focusPlus, Penny opens up about her experience trying the email tool Superhuman and the surprising lesson it revealed about resistance, flexibility, and adapting to new ways of working.If you're tired of feeling buried in email and ready to reclaim your focus, this episode is your permission slip to let go of inbox zero for good.#Productivity #InboxZero #TimeToReset #PennyZenker #Focus #EmailManagement #AIProductivity #WorkplaceEfficiency #PersonalDevelopment #MindsetShiftLove the show? Subscribe, rate, review, and share! https://pennyzenker360.com/positive-productivity-podcast/

Note: "Act 1" was a separate published audio podcast.Get an EZ "DEFECTOR" hoodie!*Check out EZ's morning radio show "The InZane Asylum Q100 Michigan with Eric Zane" Click here*Get a FREE 7 day trial to Patreon to "try it out."*Watch the show live, daily at 8AM EST on Twitch! Please click here to follow the page.Email the show on the Shoreliners Striping inbox: eric@ericzaneshow.comTopics:*Trailer for "The Crash" on Netflix*Anal pro beach volleyball?*Super Human elbow drop!*Blackbelt Nick the PA Announcing legend.*Local psycho blows up his own house in attempted murder/ suicide; only succeeds in suicide.*Will Levis' Mother promotes her son's sex tape.*Asshole of the DaySponsors:West Michigan Whitecaps, Zalenski Outdoor Services, Impact Powersports, Kuiper Tree Care, Frank Fuss / My Policy Shop Insurance, Kings Room Barbershop, Shoreliners,  Ervines Auto Repair Grand Rapids Hybrid & EV, TC PaintballInterested in advertising? Email eric@ericzaneshow.com and let me design a marketing plan for you.Contact: Shoreliners Striping inbox eric@ericzaneshow.comDiscord LinkEZSP TikTokSubscribe to my YouTube channelHire me on Cameo!Tshirts available herePlease subscribe, rate & write a review on Apple Podcastspatreon.com/ericzaneInstagram: ericzaneshowTwitterAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Note: "Act 1" was a separate published audio podcast.Get an EZ "DEFECTOR" hoodie!*Check out EZ's morning radio show "The InZane Asylum Q100 Michigan with Eric Zane" Click here*Get a FREE 7 day trial to Patreon to "try it out."*Watch the show live, daily at 8AM EST on Twitch! Please click here to follow the page.Email the show on the Shoreliners Striping inbox: eric@ericzaneshow.comTopics:*Trailer for "The Crash" on Netflix*Anal pro beach volleyball?*Super Human elbow drop!*Blackbelt Nick the PA Announcing legend.*Local psycho blows up his own house in attempted murder/ suicide; only succeeds in suicide.*Will Levis' Mother promotes her son's sex tape.*Asshole of the DaySponsors:West Michigan Whitecaps, Zalenski Outdoor Services, Impact Powersports, Kuiper Tree Care, Frank Fuss / My Policy Shop Insurance, Kings Room Barbershop, Shoreliners,  Ervines Auto Repair Grand Rapids Hybrid & EV, TC PaintballInterested in advertising? Email eric@ericzaneshow.com and let me design a marketing plan for you.Contact: Shoreliners Striping inbox eric@ericzaneshow.comDiscord LinkEZSP TikTokSubscribe to my YouTube channelHire me on Cameo!Tshirts available herePlease subscribe, rate & write a review on Apple Podcastspatreon.com/ericzaneInstagram: ericzaneshowTwitterAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Green Berets are built over time. Special Operations Truth #3: SOF cannot be mass produced. America's most elite warriors are developed through experience, through leadership, and through the responsibility of developing others. This is the job of the Special Forces Noncommissioned Officer.In this episode, Fran Racioppi sat down with retired Command Sergeant Major Rob Abernethy to dissect the evolution of the Green Beret NCO, and their officer counterparts, to show how that development shapes the effectiveness of Army Special Operations and national strategy.CSM Abernethy served nearly four decades in the Army and across special operations from a junior 18E communications sergeant, to the Command Sergeant Major of US Army Special Operations Command and United States European Command. Rob breaks down the role of the NCO as the backbone of the Regiment, the importance of regional alignment in building partner forces, and where Special Forces fits into military strategy from the pre-9/11 period, through the Global War on Terror and into today's Large Scale Combat Operations.We also explore the rapid evolution of technology and the challenge of integrating new tools without losing the fundamentals of leadership and warfighting. From artificial intelligence to modern battlefield systems, Rob emphasizes that technology must support the force, not replace the mindset that defines it.Finally, after retiring as one of the longest serving Green Berets in the Army, CSM Abernethy shares his perspective on transition after service and his current role continuing to develop soldiers through his work at AUSA.This is a conversation about leadership, evolution, and the responsibility to prepare the next generation of Green Berets for the fight ahead.HIGHLIGHTS0:00 Introduction2:00 Welcome to the Jedburgh Podcast5:20 From junior to senior NCO on an ODA15:31 Role of the Team Sergeant18:52 The culture of a Special Forces team25:02 Importance of Regional Alignment32:08 Bridging the generation gap43:14 American Military Technological Advantage49:00 Biggest Threat to America52:18 Remembering ServiceQUOTES“The average age on the teams was much older.”“Nobody says, ‘Hey, I'm going to join the Army and my goal is to be a sucky soldier.'”“The Team Sergeant is one of the most critical parts of the team.”“Over time, what you do is build confidence with the team.”“The Officer's success is really the Team's success and the Team's success is based on the Officer.”“Our confidence as a Team Sergeant needs to be projected through the team leader.”“You have to have a lot of confidence in the team you're selecting.”“The administrative stuff makes a difference.”“The little things absolutely matter.”“The more astute you are to the environment in which you're going to operate, the better you're going to be.”“In the next 10 years, it's going to be phenomenal what we actually bring to the battlefield because AI is going to make us that much better.”“The Department of War is crushing the acquisition process now.”“Our relationship with our NATO allies has been strong and needed, and still will be needed.”“One thing that stayed consistent was my desire to be good, to be an expert, and lead by example.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

Ron White is a two-time USA Memory Champion, U.S. Navy veteran, and one of the world's foremost memory training experts. Known as the "Brain Athlete," he has dedicated his career to proving that extraordinary memory is not a gift — it's a trainable skill. A Texas-based entrepreneur and speaker, White first discovered memory techniques in 1991 at age 18 and has spent over three decades mastering and teaching them. He won back-to-back USA Memory Championships in 2009 and 2010 and held the national record for the fastest to memorize a shuffled deck of cards in one minute and 27 seconds. He has appeared on the History Channel's Stan Lee's Superhumans, National Geographic's Brain Games, and Fox's Superhuman with Kal Penn and Mike Tyson, as well as Good Morning America, Fox & Friends, and CBS Evening News. After September 11th, White joined the U.S. Navy Reserve as an intelligence specialist and deployed to Afghanistan in 2007, serving until 2010. That experience inspired what he considers his most important work: memorizing the names, ranks, and order of death of more than 2,300 American service members killed in Afghanistan — over 7,000 words committed to memory over 10 months. He travels the country writing those names from memory on a 52-foot memorial wall, a tribute built on a simple message: "You are not forgotten." Today, White speaks to audiences in over 30 countries and runs Brain Athlete, where he teaches individuals and organizations to improve their memory, read faster, and learn more effectively through his flagship Black Belt Memory program. Shawn Ryan Show Sponsors: Sign up for your $1 per month trial today at https://shopify.com/srs Ready to upgrade your eyewear? Check them out at https://roka.com and use code SRS for 20% off sitewide. Start your new morning ritual & get up to 43% off your @MUDWTR with code SRS at https://mudwtr.com/SRS ! #mudwtrpod If you're serious about selling to the Department of War, go to https://SBIRAdvisors.com and mention Shawn Ryan for your first month free. Get 30% off your first subscription order at https://armra.com/srs or enter code SRS at checkout. Get 50% off your first order of Sundays for Dogs at https://sundaysfordogs.com/SRS50 or use code SRS50 at checkout. Ron White Links: IG - https://www.instagram.com/brainathlete Youtube - https://www.youtube.com/@brainathlete Facebook - https://www.facebook.com/RonWhiteMemory TikTok - https://www.tiktok.com/@realbrainathlete Website - https://www.brainathlete.com/shawn Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send us Fan MailJason Katcher is the Global Education Channel Lead at Superhuman, where he focuses on scaling AI-powered productivity and communication tools across education through strategic partnerships. Previously at Google, Dropbox, and multiple edtech startups, Jason brings deep experience in education technology, AI adoption, and go-to-market strategy.

What if every thought you've ever had, every life you've ever lived, is permanently encoded in the fabric of space-time — accessible right now?Quantum consciousness pioneer Caroline Cory joins Debbi Dachinger to reveal the mechanics behind the planetary grid, parallel incarnations, and why your original source self already knows everything about your mission here. From why karma isn't punishment to how blind people were made to see in her upcoming Superhuman 2 film, this conversation dismantles everything you thought you knew about memory, identity, and the infinite nature of who you truly are. Your past lives aren't behind you. They're happening right now.⏱ TIMESTAMPS0:00 – Memory isn't in the brain: the space-time library explained5:20 – The planetary grid: Earth's quantum memory network11:00 – Why parallel lives are more accurate than past lives17:30 – Projecting your consciousness across 10 lifetimes at once23:00 – How Caroline uses this science to access her source self28:45 – Karma redefined: unfinished soul contracts, not punishment34:10 – Pulling the best from every concurrent lifetime into now39:30 – Channeling yourself: when your higher self is the ET you're receiving44:00 – Truth coming out: UFOs, disclosure & the end of conspiracies49:20 – Superhumans & where we're headed: telepathy, gifts & the new human54:00 – Superhuman 2: making blind people see & new science of the body58:30 – How to find Caroline & what's coming next

Rahul Vorra is the founder and CEO of Superhuman, the premium email client for power users. He previously built the Gmail plug-in Reportive and sold it to LinkedIn. He began somewhere unexpected though, as a game designer on RuneScape. In this conversation, Rahul breaks down why most founders misunderstand product market fit, why premium can actually hurt your business, and how deliberate constraint can become your biggest advantage.   Follow Rahul Vohra on X: https://x.com/rahulvohra Follow Fareed Mosavat on X: https://x.com/far33d Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What if Olympic athletes could use steroids and other performance-enhancing drugs, legally? They can now, at the Enhanced Games. The Enhanced Games take place on May 24th and it’s anyone’s guess what will happen.Unless you’re Chris Gayomali, host of the new podcast SuperHuman, which is an inside look at the ‘steroid Olympics.’ Chris Gayomali joins Oz to break down how aging tanks athletes' earning potential, how the Enhanced Games strives to be like Formula One, and what drew big-money backers Peter Thiel and Donald Trump Jr. to the table. Additional Reading: SuperHuman | iHeart What Would the Olympics Be Like If the Athletes Could Juice? | GQ EXCLUSIVE NordVPN Deal ➼ https://nordvpn.com/techstuff Try it risk-free now with a 30-day money-back guaranteeSee omnystudio.com/listener for privacy information.

Dare To Dream with Debbi Dachinger CAROLINE CORY: Your Memories Aren't in Your Brain — They're Stored in the Fabric of Space-Time What if every thought you've ever had, every life you've ever lived, is permanently encoded in the fabric of space-time — accessible right now? Quantum consciousness pioneer Caroline Cory joins Debbi Dachinger to reveal the mechanics behind the planetary grid, parallel incarnations, and why your original source self already knows everything about your mission here. From why karma isn't punishment to how blind people were made to see in her upcoming Superhuman 2 film, this conversation dismantles everything you thought you knew about memory, identity, and the infinite nature of who you truly are. Your past lives aren't behind you. They're happening right now. Topics: – Memory isn't in the brain: the space-time library explained – The planetary grid: Earth's quantum memory network – Why parallel lives are more accurate than past lives – Projecting your consciousness across 10 lifetimes at once – How Caroline uses this science to access her source self – Karma redefined: unfinished soul contracts, not punishment – Pulling the best from every concurrent lifetime into now – Channeling yourself: when your higher self is the ET you're receiving – Truth coming out: UFOs, disclosure & the end of conspiracies – Superhumans & where we're headed: telepathy, gifts & the new human – Superhuman 2: making blind people see & new science of the body – How to find Caroline & what's coming next ABOUT THE GUEST: CAROLINE CORY Caroline Cory is a quantum consciousness researcher, filmmaker, author, and founder of Omnium Universe — a cutting-edge platform exploring the science of consciousness, multidimensional reality, and human potential. With over 20 years of teaching experience, Caroline has pioneered methods for accessing the source self, understanding the mechanics of spacetime, and activating superhuman abilities. She is the creator of the groundbreaking documentary Superhuman, and is currently completing its highly anticipated sequel Superhuman 2, featuring extraordinary new science about the body — including documented cases of blind people being made to see. Caroline's work bridges quantum physics, galactic history, and practical consciousness evolution.

The conditions service members live in directly affect Military readiness and national security. It's the responsibility of Congress to authorize military funding to ensure the warfighter has what they need in combat and at home. Every decision impacts the strength of the force and their families.In this episode, Fran Racioppi sat down with Representative Mike Levin, who serves California's 49th District and sits on the House Appropriations Committee, Subcommittee on Military Construction and Veterans Affairs to discuss the policies and decisions shaping today's military bases. From investments in infrastructure at Camp Pendleton to broader oversight of Veterans Affairs, Congressman Levin outlines why improving living conditions, facilities, and support systems is essential to maintaining a ready and capable force.Our conversation explores the responsibility of leadership to develop a culture where reporting substandard conditions is encouraged. We also discuss the broader role of Congress in overseeing military operations, and the importance of transparency, strategy, and accountability when American forces are deployed.Congressman Levin shares his perspective on the war with Iran, his views on the need for checks and balances, and the growing divide that has made bipartisan governance more difficult. He emphasizes that strong institutions require leaders willing to put mission over politics and to ensure that the constitutional framework guiding military action is upheld.This is a conversation about leadership, accountability, and the systems that support those who serve. It is about ensuring readiness not just on the battlefield, but across the entire force.Highlights:0:00 Introduction1:53 Welcome to the Jedburgh Podcast3:19 California's 49th District6:34 Improving Military Housing14:25 Status of the Iran War19:37 Is Iran A Direct Threat To The US?22:08 Iran's State Sponsorship of Terrorism25:20 Negotiating with Iran28:41 Bridging the GapQuotes:“It is imperative that we treat our veterans and military families with absolute respect.”“We've got real issues with barracks.”“We're not looking for the Ritz Carlton. We're just looking for a decent place.”“The average member of the military needs a decent place where they can live.”“The challenge is the lack of clarity about what they're being asked to do.” “They didn't brief us on what the plan was going to be.”“It's a war that is unauthorized. It is a war without a clear exit plan.”“What damage have we done to our allies around the world? A lot.”“We know less today than we did before the war began.”“The question is whether or not the military has actually made it a worse problem or has it actually ameliorated the problem.”“The Iranians have been a horrible regime.”“I don't think the President has enough people around him telling him what he needs to hear, not what he wants to hear.”“Use of military force should be last resort always.”“I am personally never going to see the other side as my enemy. I see them as my political opponent.”“Running the United States is not an easy challenge.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.The opinions presented on the The Jedburgh Podcast and the Jedburgh Media Channel are the opinions of guests and host Fran Racioppi. They do not necessarily reflect the opinions of the Green Beret Foundation and the Green Beret Foundation assumes no liability for their accuracy, nor does Green Beret Foundation endorse any political candidate or any political party.

Nick agreed to personally set up your Orgo in a 15 min call: https://startup-ideas-pod.link/orgo_ai I sit down with Nick from Orgo to break down exactly how to run a one-person AI agent business that can realistically clear a few million dollars a year. Nick walks through the offer, the verticals worth chasing, the full software stack, and the live setup of an agent that manages other agents. We focus on tactics over theory, with specific tools, pricing, and the playbook for landing customers as a solopreneur. By the end, anyone with solid AI fluency will have a clear path from offer design to fulfillment. Timestamps 00:00 – Intro 02:54 – Designing the AI Agent Business Offer 06:38– Selling an AI Employee, Not an Agent 07:26 – Industries to Target (and Two to Avoid) 14:54 – Content Is Overpowered and How to Get Customers 17:51 – The Customer-Facing Tool Stack 20:49 – Building Agents Stack 25:51 – Model Picks: GPT 5.5, GLM 5.1, Kimmy, Opus 4.7 27:08 – Nick's Stack 28:14 – Why Obsidian Is the Second Brain Layer 30:22 – Live Walkthrough: Spinning Up a Cloud Computer in Orgo 33:53 – Cloud Computers vs. Mac Minis 38:37 – Building Agents and Structuring Workspaces for Customers 43:56 – Watchdogs, Observability, and Reliability 45:28 – Closing Thoughts on the Solopreneur Era Key Points Sell unlimited agents, unlimited usage, and unlimited support to remove friction; most customers actually use one to three agents. Avoid healthcare and finance to start; focus on legacy verticals like marketing, law, insurance, manufacturing, wholesale, and real estate. OpenClaw agents go for around 5K a month; Hermes agents can go for 10K a month. The full stack: Granola, Trello, Loom, Superhuman, Asana, Codex, Hermes, Orgo, Composio, Agent Mail, and Obsidian. GPT 5.5 is the recommended default model for tool calling; GLM 5.1 and Kimmy work for lighter tasks; Opus 4.7 fits long-horizon coding. Use agents to set up other agents — pair Cloud Code or Codex with MCPs like Perplexity, Context7, and X MCP for live docs. The #1 tool to find startup ideas/trends - https://www.ideabrowser.com LCA helps Fortune 500s and fast-growing startups build their future - from Warner Music to Fortnite to Dropbox. We turn 'what if' into reality with AI, apps, and next-gen products https://latecheckout.agency/ The Vibe Marketer - Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/ FIND ME ON SOCIAL X/Twitter: https://twitter.com/gregisenberg Instagram: https://instagram.com/gregisenberg/ LinkedIn: https://www.linkedin.com/in/gisenberg/ FIND NICK ON SOCIAL Youtube: https://www.youtube.com/@nickvasiles Instagram: https://www.instagram.com/nickvasilescu/ Personal Website: https://www.nickvasilescu.com/

Superhuman Mail users respond to 72% more emails per hour and save an average of four hours every week — numbers backed by a case study from one of the Big Three strategy consulting firms. Rahul Vohra, CEO at Superhuman Mail, built the world's fastest email engine over three years without launching, held the line until the product was ready, and then productized product-market fit into a repeatable, measurable science. Following Superhuman's acquisition by Grammarly in 2025, Rahul is now steering the company toward a unified AI-native productivity suite spanning email, calendar, tasks, and agents.What you'll learn:The 5-step PMF Engine: how to survey, segment, analyze, implement, and track your way to product-market fit with a numerical scoreWhy you should ignore the not disappointed and most somewhat disappointed users — and which signals actually tell you who to build forHow to use the High Expectation Customer (HXC) framework to narrow your market without changing your productWhy PMF is a moving target and how to defend it against commoditization and copy-cat competitionHow Rahul operates as the editor of the product — using 20 verbatim quotes to push PMs and designers to sharper decisionsKey takeaways:If more than 40% of your users would be very disappointed without your product, you have an initial PMF — and you can measure your way thereChanging your market is faster than changing your product — segmentation alone can jump your PMF score 10 points overnightBuilding for your highest-expectation customer is not the same as building for your ICP — confuse the two, and you'll optimize for the wrong signalCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Rahul VohraSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

The secret to better communication isn't adding more—it's knowing what to leave out.Communication isn't clearer when you say more — it's clearer when you say less. As David Epstein puts it, we're wired to keep adding, even when “the better solution is often what you take away.” The challenge isn't having ideas; it's choosing which one actually matters.Epstein is an author and investigative journalist known for his New York Times bestseller Range. In his latest book, Inside the Box, he explores how constraints can sharpen creativity and elevate thinking, a theme that reflects his broader work at the intersection of psychology, performance, and innovation. “If you assume someone will only remember one thing,” he explains, “decide what that is before you start talking.” That simple constraint forces clarity — and changes how we communicate entirely.In this episode of Think Fast Talk Smart, Epstein and host Matt Abrahams unpack why limits make us better communicators and thinkers. From the dangers of “featuritis” to the creative breakthroughs sparked by restriction, they explore how blocking familiar paths leads to more original ideas and communication. To listen to the extended Deep Thinks version of this episode, please visit FasterSmarter.io/premium.Episode Reference Links:David EpsteinDavid's Book: Inside the BoxEp.108 All In: How Improv Helps You Show Up and Communicate Well Connect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (02:18) - Featuritis & Overload (03:57) - Constraints & Creativity (08:07) - Chunking Information (09:28) - Familiarity & Innovation (10:30) - Clarifying Through Feedback (13:01) - Defining the Problem (14:23) - Precluding Default Approaches (16:03) - The Final Three Questions (23:12) - Conclusion ********Thank you to our sponsors.  These partnerships support the ongoing production of the podcast, allowing us to bring it to you at no cost.Unleash your Superhuman potential with AI that meets you where you work. Learn more at superhuman.comJoin our Think Fast Talk Smart Learning Community and become the communicator you want to be. 

Noam Lovinsky is the CPO of Superhuman, formerly a product leader at YouTube and Meta. In this episode from Product Faculty AI CXO Podcast, Noam breaks down what it actually takes to build an AI-native organization, and why most companies are getting it completely wrong. We cover the Grammarly to Superhuman rebrand, how you trade 16 years of brand equity for a bigger bet, what "model to pixel" execution really means at 100 billion LLM calls a week, and why Noam now requires every candidate to demo AI live in their interview. This is not a conversation about AI tools. It's about what fundamentally changes when the cost of execution heads toward zero, and what that means for every leader, PM, and builder right now. What we cover: - The #1 mistake companies make when rolling out AI top-down - Why every PM on Noam's team is expected to push code to production - How Superhuman restructured hiring around live AI fluency - What a world-class PM does that AI still cannot - The one thing Noam would tell every executive in the world right now - Why long-term planning is the first mental model you need to throw out Who this is for: Founders, C-suite executives, product leaders, and ecommerce operators trying to understand what AI agents mean for their business right now. Subscribe for weekly conversations with top executives navigating the AI era. https://www.youtube.com/@productfaculty  #ShopifyAI #AgenticCommerce #AIAgents #FutureOfEcommerce #AIShoppingAgents #Shopify #EcommerceStrategy #AICXOPodcast #AIForBusiness #ProductLeadership #CommerceProtocol #USDC #CryptoPayments #AIRetail #ManiShopify

There is a steady stream of headlines shaping how Veterans view the Department of Veterans Affairs. Disability benefits are being cut. The VA is being privatized. Programs are disappearing. That is the narrative. But is it the reality?In a social media environment driven by clicks, likes, and engagement, information spreads fast, and too often no one stops to ask whether it is actually true. When it comes to healthcare, benefits, and the systems Veterans rely on, the facts matter.In this episode, Secretary of Veterans Affairs Doug Collins joins Fran Racioppi to address those concerns directly and bring clarity to what is actually happening inside the VA. This is not a surface level conversation. It's a direct response to the questions Veterans are asking right now.We break down the proposed disability rating regulation enforcement that rocked the Veteran community, what it was intended to do, how it was misinterpreted, and why it was withdrawn within days. We discuss the rollout of the VA's electronic health record modernization, what's working, what still needs to improve, and how it will impact care moving forward.Secretary Collins also addresses the reality of community care and the claims surrounding privatization, clarifying how the VA will always deliver and fund care for Veterans. We talk about workforce challenges, hiring, and the responsibility to ensure Veterans are receiving timely and effective support with a right-sized VA staffing level.The conversation also focuses on one of the most critical issues facing the Veteran community: suicide prevention. With the majority of Veterans not currently engaged with the VA, the approach must evolve. Outreach must expand, accountability must increase, and programs must show measurable results.Finally, we cover housing stability through VA home loan programs and the responsibility to ensure Veterans have real options to maintain their homes, but also understand they have a personal responsibility for the financial decisions they make.This conversation is about clarity and accountability. Because at the end of the day, the mission is simple - deliver results for Veterans.Highlights0:00 Introduction2:31 Welcome to the Jedburgh Podcast3:31 Dispelling Disability Rating Misconceptions10:43 Running A Wartime VA16:24 Electronic Health Record Modernization20:09 Is the VA Privatizing Healthcare?27:51 VA Employee Moral34:22 Cutting the VASP Program39:06 Preventing Fraud43:13 Veteran Suicide PreventionQuotes“No one that already had a disability rating was ever going to lose anything.”“I take full responsibility.”“Nobody's getting judged differently.”“We're the largest integrated healthcare system in the country. We don't act like it.”“There's no plan for privatization.”“80% of all new doctors go through the VA in some form.”“Privatization is thrown around to scare employees and veterans.”“We're never going to privatize. Definitely not under my watch. And there's no mechanism to privatize.”“There are people invested in a broken system.”“I have to compete for doctors and nurses with every hospital in the country.”“Our problem was we had too many people in the wrong places.”“What are you doing that's stupid?”“60% of death by suicide by Veterans have not had any contact with the VA.”“The VA many times was more concerned about itself than we were about actually finding metrics for the veteran.” “Capitol Hill has become more driven by the five minute YouTube clip.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

This is Nick Statt, senior producer on Decoder. We last ran a mailbag episode during the holidays, and we decided it was a good idea to do that kind of thing more often. So we're back with Nilay as the guest, answering questions and responding to feedback, criticism, and suggestions. We talk through some recent controversial episodes like our interviews with the CEOs of Superhuman and Puck, and we also discuss how we're covering AI, thinking about the future of the show, and what it takes to win (and lose) Decoder.  Links:  Nilay answers your burning Decoder questions | Decoder Mailbag (2025) Answering your biggest Decoder questions | Decoder Mailbag (2024) Confronting the CEO of the AI company that impersonated me | Decoder Can Puck reinvent the news business for the influencer age? | Decoder The people do not yearn for automation | Decoder Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt and edited by Ursa Wright. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

What stops you from speaking up when it matters most?This week on Think Fast Talk Smart, we're featuring a special episode from TED Business. Healthcare leader Sarah Crawford-Bohl offers a practical, compassionate framework to have difficult conversations with clarity and heart — and shows how it can lead to stronger teams and real impact.TED Business is a podcast from TED that offers you a new idea and perspective for any business conundrum — whether you want to learn how to land that promotion, set smart goals, undo injustice at work, or unlock the next big innovation. Every Monday, host Modupe Akinola of Columbia Business School presents the most powerful and surprising ideas that illuminate the business world. After the talk, you'll get a mini-lesson from Modupe on how to apply the ideas in your own life — because business evolves every day, and our ideas about it should, too. Listen wherever you get your podcasts or here.Episode Reference Links:TED Business Connect:Premium Signup >>>> Think Fast Talk Smart PremiumEmail Questions & Feedback >>> hello@fastersmarter.ioEpisode Transcripts >>> Think Fast Talk Smart WebsiteNewsletter Signup + English Language Learning >>> FasterSmarter.ioThink Fast Talk Smart >>> LinkedIn, Instagram, YouTubeMatt Abrahams >>> LinkedInChapters:(00:00) - Introduction (02:46) - If Not You, Then Who? (04:01) - The Cost of Silence (05:25) - Avoiding Conflict at Work (06:20) - Why Speaking Up Matters (07:30) - Building Courage Through Practice (08:40) - A Moral Compass for Conversations (12:01) - Handling Tough Feedback (17:41) - QORC Apology Framework (19:31) - Conclusion ********Thank you to our sponsors.  These partnerships support the ongoing production of the podcast, allowing us to bring it to you at no cost.Unleash your Superhuman potential with AI that meets you where you work. Learn more at superhuman.comJoin our Think Fast Talk Smart Learning Community and become the communicator you want to be. 

He ran across America. He held the record for the Death Valley Badwater Run; 146 miles in upwards of 117 degree heat. Motivational speaker, world record athlete, possible SUPER-HUMAN! Enjoy this marathon of an interview with Croix Sather!Follow his Journey: CroixSather.comCroix's YouTube Channel: youtube.com/user/CROIXsatherEmail Us: Info@amateurhourpod.comSocials: @Amateur_Pod

From building Applied Intuition from YC-era autonomy tooling into a $15B physical AI company, Qasar Younis and Peter Ludwig have spent the last decade living through the full arc of autonomy: from simulation and data infrastructure for robotaxi companies, to operating systems for safety-critical machines, to deploying AI onto cars, trucks, mining equipment, construction vehicles, agriculture, defense systems, and driverless L4 trucks running in Japan today. They join us to explain why “physical AI” is not just LLMs on wheels, why the real bottleneck is no longer model intelligence but deployment onto constrained hardware, and why the future of autonomy may look less like one-off demos and more like Android for every moving machine.We discuss:* Applied Intuition's mission: building physical AI for a safer, more prosperous world, powering cars, trucks, construction and mining equipment, agriculture, defense, and other moving machines* Why physical AI is different from screen-based AI: learned systems can make mistakes in chat or coding, but safety-critical machines like driverless trucks, autonomous vehicles, and robots need much higher reliability* The evolution from autonomy tooling to a broad physical AI platform: starting with simulation and data infrastructure for robotaxi companies, then expanding into 30+ products across simulation, operating systems, autonomy, and AI models* Why tooling companies came back into fashion: Qasar on why developer tooling looked unfashionable in 2016, why Applied Intuition still bet on it, and how the AI boom made workflows and tools central again* The three core buckets of Applied Intuition's technology: simulation and RL infrastructure, true operating systems for vehicles and machines, and fundamental AI models for autonomy and world understanding* Why vehicles need a real AI operating system: real-time control, sensor streaming, latency, memory management, fail-safes, reliable updates, and why “bricking a car” is much worse than bricking an iPad* Physical machines as “phones before Android and iOS”: Peter explains why today's vehicle and machine software stack is fragmented across many operating systems, and why Applied Intuition wants to consolidate the platform layer* Coding agents inside Applied Intuition: Cursor, Claude Code, internal adoption leaderboards, and how AI tools are changing engineering workflows even in embedded systems and safety-critical software* Verification and validation for physical AI: why evals get harder as models improve, how end-to-end autonomy changes simulation requirements, and why neural simulation has to be fast and cheap enough to make RL practical* From deterministic tests to statistical safety: why autonomy validation is shifting from binary pass/fail requirements toward “how many nines” of reliability and mean time between failures* Cruise, Waymo, and public trust: Qasar and Peter discuss why autonomy failures are not just technical issues, how companies interact with regulators, and why Waymo is setting a high bar for the industry* Simulation vs. reality: why no simulator perfectly represents the real world, how sim-to-real validation works, and why real-world testing will never disappear* World models for physical AI: hydroplaning, construction equipment, visual cues, cause-and-effect learning, and where world models help versus where they are not enough* Onboard vs. offboard AI: why data-center models can be huge and slow, but onboard vehicle models need millisecond-level latency, low power, small size, and distillation-like efficiency* Why physical AI is not constrained by model intelligence alone: the hard part is deploying models onto real hardware, under safety, latency, power, cost, and reliability constraints* Legacy autonomy vs. intelligent autonomy: RTK GPS in mining and agriculture, why hand-coded path-following worked for decades, and why modern systems need perception and dynamic intelligence* Planning for physical systems: how “plan mode” applies to robotaxis, mining, defense, and multi-step physical tasks where actions change the state of the world* Why robotics demos are not production: the brittle last 1%, humanoid reliability, DARPA Grand Challenge-style prize policy, and the advanced engineering gap between research and deployment* Applied Intuition's hard-earned lessons: after nearly a decade, Peter says they can look at a robotics demo and predict the next 20 problems the company will hit* Qasar's advice to founders: constrain the commercial problem, avoid copying mature-company strategies too early, and remember that compounding technology only matters if you survive long enough to see it compound* Why 2014 YC advice may not apply in 2026: capital markets, AI company dynamics, and the difference between building in stealth with a deep network versus building as a new founder today* What Applied is hiring for: operating systems, autonomy, dev tooling, model performance, evals, safety-critical systems, hardware/software boundaries, and engineers with deep curiosity about how things workApplied Intuition:* YouTube: https://www.youtube.com/@AppliedIntuitionInc* X: https://x.com/AppliedInt* LinkedIn: https://www.linkedin.com/company/applied-intuition-incQasar Younis:* X: https://x.com/qasar* LinkedIn: https://www.linkedin.com/in/qasar/Peter Ludwig:* LinkedIn: https://www.linkedin.com/in/peterwludwig/Timestamps00:00:00 Introduction: Applied Intuition, Physical AI, and 10 Years of Building00:01:37 Physical AI vs. Screen AI: Why Safety-Critical Changes Everything00:02:51 The Origin Story: Tooling, YC, and the Scale AI Comparison00:05:41 The Three Buckets: Simulation, Operating Systems, and Autonomy Models00:11:10 Hardware, Sensors, and the LiDAR Question00:14:26 The Operating System Layer: Why Vehicles Are Like Pre-Android Phones00:19:13 Customers, Licensing, and the Better-Together Stack00:21:19 AI Coding Adoption: Cursor, Claude Code, and the Bimodal Engineer00:26:41 Verifiable Rewards, Evals, and Neural Simulation00:31:04 Statistical Validation, Regulators, and the Cruise Lesson00:40:25 World Models, Hydroplaning, and Cause-Effect Learning00:43:34 Onboard vs. Offboard: Latency, Embedded ML, and Distillation00:50:57 Plan Mode for Physical Systems and Next-Token Prediction Universally00:53:04 Productionization: The 20 Problems Every Robotics Demo Will Hit00:58:00 Founder Advice: Constraints, Compounding Tech, and Mature-Company Mimicry01:05:41 Hiring Philosophy: Hardware/Software Boundary and Engineering Mindset01:08:50 General Motors Institute, Education, and the Curiosity MindsetTranscriptIntroduction: Applied Intuition, Physical AI, and 10 Years of BuildingAlessio [00:00:00]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: And today we're very honored to have the founders of Applied Intuition, Qasar and Peter. Welcome.Qasar [00:00:17]: You guys really know how to turn it on to podcast mode. That was, you guys are real pros at this.Qasar [00:00:23]: They were just joking around right before this, and then they flipped it pretty quick.Alessio [00:00:29]: Oh, yeah, it's good to have you guys. Maybe you just wanna introduce yourself so people know the voice on the mic and they'll know what they're hearing.Peter [00:00:33]: Oh, sure. Yeah, I'm Peter Ludwig. I'm the co-founder and CTO of Applied Intuition.Qasar [00:00:38]: And my name is Qasar Younis. I am the CEO and co-founder with Peter.Alessio [00:00:42]: Nice. Can you guys give the high-level overview of what Applied Intuition is? And I was reading through some of the Congress files, when you went out there, Peter, and eighteen of the top twenty global non-Chinese automakers, you two guys, you have customers in agriculture, defense, construction. I think most people have heard of Applied Intuition tied to YC when it was first started, and then you were kinda in stealth for a long time, so maybe just give people the high-level overview of what it is today, and then we'll dive into the different pieces.Peter [00:01:10]: Yeah. So at Applied Intuition, our mission is to build physical AI for a safer, more prosperous world. And so we work on physical AI for all different types of moving systems, everything from cars to trucks to construction and mining equipment, to defense technologies. And we're a true technology company, so we build and sell the technology, and we sell it to the companies that make the machines. We sell it to the government, really anyone that wants to buy a technology to make machines smart.Physical AI vs. Screen AI: Why Safety-Critical Changes EverythingQasar [00:01:38]: Yeah. And I think in the broader AI landscape, a lot of the focus, rightfully so in the last, three years has been on large language models, and so everything fits in a screen. Like, whether it's code complete products or things like that. And what's different about us is we're deploying intelligence onto a lot of things that don't have screens. they're physical machines. There are sometimes screens within the cabin or for example of a car or a truck or something like that, but most of the value we provide is putting intelligence that is in safety critical environments. So that those two words are really important because learn systems can make mistakes if you're asking for, like, some, so something like, “Tell me about these podcast hostsQasar [00:02:28]: that I'm about to go meet.” But you can't do that obviously when you run, like, as an example, we run driverless trucks in Japan right now, as we speak. We can't have errors. Those are L4 trucks. Yeah.Alessio [00:02:40]: Yeah. Was that always the mission? I remember initially, I think people put you and Scale AI very similarly for some things about being kinda like on the data infrastructure side of things. What was the evolution of the company?The Origin Story: Tooling, YC, and the Scale AI ComparisonPeter [00:02:51]: Well, from the very beginning, we always wanted to, really be a technology company that helped generally push forward the industrial sector. And so we started off working in autonomy. Our very first customers were robotaxi companies. And we started off doing a lot of work in simulation and data infrastructure. And then over the years, we've expanded our portfolios. Now we have, over thirty products, and it's a pretty broad technology play within the landscape of physical AI.Qasar [00:03:19]: Yeah, I think the Scale reason is because we're all YC Universe companies. But it was a very different company. Scale, was, is more of a services company, data labeling company fundamentally. We started and still are, do a lot of tooling. So like, you think developer tooling is now in vogue again, thanks to the AI boom. But honestly, ten years ago, it was out of vogue. It w Like, doing a tooling company in 2016, 2017 was not, like, the thing to do because, I don't know if you remember, the VCs generally, their views was that toolings are They're just workflows, and workflows ultimately are not really interesting. And we've gone and come, full circle with that. But when we started the company, our kind of it's kinda like in the periphery of what the company wants to be. It was like, from our earliest days, like, we wanna deploy software on physical machines, like on cars and on trucks and things like that. And obviously, we didn't know that the transformer boom was gonna happen. We didn't know that autonomy systems would become end-to-end. Those things we didn't know. And why that's important when autonomy systems become end-to-end, it is just now those models can be generalized to, multiple form factors. And so back nine, ten years ago, tooling was a great way, and still is a great way to, build the technology and sell technology to our end customers, a lot of them who wanna build this stuff themselves. And so we just offer like a spectrum of solutions from you can just use like one part of a development suite of tools all the way to buying the full thing. The way to think about the company, or at least the way we think about the company is, as Peter said, a technology provider. It's kinda like, what NVIDIA does or what an AMD, but we just don't do chips.Qasar [00:05:06]: We don't do silicon. But we're a technology provider fundamentally. And I think even, we used to joke when we started the company, like, we're not the guys to build, like, Instagram. Like that was just towards That's not our That's just not us in a most fundamental way. IAlessio [00:05:20]: You have thoughts.Qasar [00:05:21]: Yes.Qasar [00:05:22]: Well, it's, it's I mean, I think it's just like what And I mean, we worked on Maps and stuff, Google Maps. Consumer products are extremely difficult for a lot of different reasons. It just, I think doesn't scratch the itch. I think we're like Michigan guys who are kind of more of that traditional engineering kind of a realm, or lineage. we used to jokeThe Three Buckets: Simulation, Operating Systems, and Autonomy ModelsPeter [00:05:41]: I gotta say, though, what was clear ten years ago was that there was so much more that was possible with software and AI in vehiclesPeter [00:05:47]: and that was generally the space that we started in ten years ago.Peter [00:05:51]: And the precise path that we've taken over the years, I think we've been strategic, and we've adjusted to make sure that we're actually building stuff that's valuable to the market. And like, the technology has changed so much. Like our own technology stack has completely changed, I would say, roughly every two years. And so now we've probably done, let's say, four complete evolutions of our own technology stack. And I sort of see that cadence roughly keeping up.Peter [00:06:13]: And so the way even we think about engineering is almost on this two-year horizon, we're preparing ourselves that, hey, like, we wanna invest the appropriate amount, but then also be very dynamic as the research gets published and as our research team figures out new advancements and adapting to that.Qasar [00:06:27]: Yeah. One thing that has been consistent is the type of people we've, we've recruited. It's engineers who are fall into the sometimes very traditional, like, GoogleQasar [00:06:38]: -gen suite, but way different from, other companies. We are hiring folks who really know the intersection of hardware and software, who know really low-level systems. Obviously, traditional ML researchers and folks who've, actually, put ML systems into production. That's been pretty consistent. I think that, like, you look at the mix of our engineering, eighty-three percent of the company is engineering, so it's, like, a giant list.Qasar [00:07:05]: A lot of engineers.Alessio [00:07:06]: Which, by the way, a thousand engineersQasar [00:07:07]: Yeah. A thousand engineers.Alessio [00:07:08]: that's on your website, so I imagine it's up to date.Qasar [00:07:11]: It is, it is up to date, yes. Yes.Alessio [00:07:12]: okay. And then forty-plus founders.Qasar [00:07:15]: Yeah. We would tend to also, This was more luck than strategy. But we've recruited a lot of ex-founders. It's been a great place for founders, YC and non, ‘cause obviously I know a lot of the YC folks. It's kind of like we recruit a lot of Google people.Qasar [00:07:33]: For them to exercise both their technical and non-technical skills because, we're, we're, we're on the applied side. We have a research team that we do fundamental research, we publish, and we've, we've had great traction there. But fundamentally, the business wants to take this intelligence and deploy it into production and there's, like, a certain type of person that's more interested in that.Alessio [00:07:54]: Yeah. You mentioned the tech stack, Peter, so I just wanted to give you some rein to just go into it. I'm interested in where Wayve Nutrition, starts and ends in some sense, what won't you do? What, do you do that's common among all the verticals that you cover?Peter [00:08:10]: There's a few buckets of work that we do, and we've been at this for almost ten years now, so the technology's pretty broad. But we got startedQasar [00:08:17]: Yeah, with a thousand engineers, like, you could work on lots of things.Peter [00:08:19]: There's lots of stuff, yeah, espe-especially with AI tools to help.Peter [00:08:22]: So we got our start in simulation and simulation tooling and infrastructure. And so generally, if you're trying to build a very complex software system that involves moving machines, you need to test that, and the best way to test it is it's a combination of virtual developments, a simulation, and then also obviously real world testing.Peter [00:08:39]: And then there's a very careful process of that correlation between the simulation results and the real world results and ensuring that the simulator is in fact accurate to that. Simulation's a very deep topic.Peter [00:08:49]: We have a whole suite of products in that, and we could talk for many hours about that specifically. But that is one part of what we do as a company. Reinforcement learning as a subpart of that is also super critical. I think a lot of the a lot of the best advancements happening in a lot of these AI systems right now in some way relate to reinforcement learning, and with now we have lots of compute, and you can do tons of interesting things for reinforcement learning. The second bucket of work that we do is on operating systems technology. true operating systems. Like, think about, schedulers and memory management and middleware and message passing and highly reliable networking and data links. Like, the reality is, if you want to deploy AI onto vehicles, you need a really good operating system. And when we were getting deeper into that space, there wasn't really anything that we were happy with.Peter [00:09:39]: Like, things existed, absolutely, and we were using what was available in the market, and as an engineering organization, we roughly realized these things aren't great. We think we can do this better, and so let's, let's build something. And that was then the that was the moment of inspiration that started our operating systems business, which is now a very real business for us. And in order to write and run great AI, you need a great operating system, and so that-that's what got us into that. And then the third bucket that we work on, it's, it's true fundamental AI technology. Models, we do a lot of work in, as mentioned, the foundational research, but then the also the world models and the actual autonomy models that are running on these physical machines, and that's across cars, trucks, mining, construction, agriculture, and defense, and so that's both land, air, and sea.Qasar [00:10:31]: And also, a smaller subsector of that third bucket is the interaction of humans with those machines.Qasar [00:10:38]: So that's a multimodal, experience. Historically, if you're moving a dirt mover or any of these machines, there are, like, buttons you press, whether they're actual physical tactile buttons or something like a touch screen. That's just That fundamentally is changing to where you're just talking to the machine and the machine and you're teaming with the machine.Alessio [00:10:58]: Voice?Qasar [00:10:59]: Yeah, voice, absolutely, yeah.Alessio [00:11:00]: Oh.Qasar [00:11:00]: And also the machine just being aware of who is in the cabin, what their state is. you can think from a safety systems perspective, the most simple version of this is, like, the driver is tired, right? They're, they're if you get those alerts when you're driving your car and saysHardware, Sensors, and the LiDAR QuestionQasar [00:11:15]: -maybe take a coffee break, that take that times, a couple of order of magnitudes up. But this concept of teaming man and machine is important. When you think about running agents or just running, different instances of, Claude and doing work for you in the background, you can take that analogy out, almost copy and paste and put it into, like, a farm, where you have a farmer who's running a number of machines. So where they interact with the machine is where there's maybe a critical decision or a disengagement or something like that, but generally speaking, the agent on the physical machine is running and making decisions on the behalf of the farmer until there's something maybe critical. And that's also what we work on. So that's not pure autonomy. It's a little bit of a mix, but it falls under, autonomy. In the automotive sense, that's typically defined in SAE levels as an L2++ systemQasar [00:12:05]: -with a human in the loop. But just take that idea, to other verticals.Alessio [00:12:09]: Yeah. You've not mentioned hardware at all, like sensors or obviously we you mentioned you don't do chips. I think even in AV there's, like, a big, cameras versus lidars. Like, what are, like, in your space maybe some of those design decisions that you made, and are they driven by the OEM's ability to put things on the machinery? And like, how much influence do you guys have on co-designing those?Peter [00:12:32]: Yeah. So we don't make sensors. Like, we're, we're not a manufacturer. Obviously, we use a lot of sensors in our autonomy products. in terms of what actually goes on the vehicles, we have a preferred set of sensors that we, let's say fully support, and then our customers, they can sort of choose from those. And obviously if there's a very strong opinion on supporting something else, we'll add that to the platform as well. And the lidar question is at this point sort of the age-old,Peter [00:12:59]: topic in autonomy, and the state of the industry right now is lidar is hands down a useful sensor, specifically for data collection and the R&D phase of autonomy development. if you see, for example, a Tesla R&D vehicle, it actually has lidar on itPeter [00:13:17]: to this day, right? In the Bay Area we see these. you'll see, like, Model Ys or Cybercab that have lidars on them just driving around. So it's, it's useful because it gives you per pixel depth information. So if you can pair a lidar with a camerand you can say that, well, this camera's looking this direction, this lidar's looking this direction, and now for each pixel of the camera I can see how far away is that pixel. you can actually then use that as a part of your model training, and then the that depth information then becomes a learned, a learned state of the camera data. And then when you're doing the production system, you can now remove the lidarPeter [00:13:52]: and now you can actually get depth with just the camera. And so that difference between, like, a highly sensored R&D vehicle and then the down-costed production vehicle, we use that across our whole portfolio of products. And of course the end goal is you want super low cost and super reliable.Peter [00:14:08]: And then in certain use cases you have some more, bespoke things. Like in defense as an example, you do things at night oftentimes, and so you care about sensors like infrared, more so than And you don't, you don't wanna be putting energy out, so you don't wanna use lidar or radar.Peter [00:14:23]: but you still need to be able to see at nighttime. So yeah, we work the whole gamut.The Operating System Layer: Why Vehicles Are Like Pre-Android PhonesAlessio [00:14:27]: Cool. So that's kinda like on the hardware level. Then on the OS level, how does that look like? What is, like, unique? my drive- I drive a Tesla. Whenever I drive some other car that has a screen, it always sucks.Alessio [00:14:38]: It's on, like, cheap Android tablet. It's like, it's laggy and all of that. What does the OS of, like, the autonomy future look like?Peter [00:14:46]: When most people, it's really what you just described. When you think about operating system in a vehicle, you're thinking about the HMI, right? The human machine interface, and absolutely that's a an important part of it, but that's actually only one thin layer on top. So when we talk about operating systems for, like, AI in vehicles, there's many layers that go deep into the CPU critical realm and embedded systems, and you're talking about the real time control ofPeter [00:15:13]: let's say the electric motors or the engine and the actuators, and you have different redundancies for different, let's say, the steering actuation in the vehicle. And all of these things, need very core support in the in the operating system. And then of course for autonomy you have real time sensor data that's streaming in, and the latencies there are really important, right? If you try to Imagine you try to run Microsoft WindowsPeter [00:15:35]: like streaming your sensor data in or controlling the vehicle. Like, the latencies are gonna be absurd. Like, you can never do that. And so what's special about what we do is we really have this system level thinking, right? So we're looking at, we care about every performance characteristics of the entire system, and then we also, because we're doing a lot of the software or all of that software, we can fine-tune and control all of those things. So we can very carefully tune in the latencies for every aspect of the system. We can carefully tune in the memory management. We can have the right, fail-safes and fallbacks, for different things. ‘Cause you have to account for what if, what if there is a critical failure? What if there's a cosmic ray that flipsPeter [00:16:14]: a bit in the middle of the processor that causes some, malfunction? And you have to have a fail-safe to all of that, and so the core operating system is a part of that. And then the one last thing, which is a lot less exciting but is, actually a very big topic, is reliability of updates.Peter [00:16:30]: so the I have a Tesla and you get updates fairly frequently, right?Peter [00:16:36]: Once a month. Most companies that are making vehiclesPeter [00:16:40]: are basically never doing updates, and they're And even if they are doing updates, they're usually only updating maybe one module. Maybe they're updating the HMI module. But they're not able to update, let's say, the CPU critical parts of the system.Peter [00:16:51]: You have to go into the dealer for that. And so with our operating system now we can actually enable highly reliable updates of any system in the vehicle, and that's way easier said than done. Like, there's lots of technical, technically deep stuff, in the tech stack to do that in a way that you're not going to accidentally brick a vehicle.Peter [00:17:08]: And right? If, imagine yourAlessio [00:17:10]: That would be bad.Alessio [00:17:11]: Bad.Peter [00:17:11]: Bricking a car is a very expensivePeter [00:17:13]: and honestly, like across the industry maybe one of the most just pure impactful things that we've done is we've just, we're, we're now enabling the industry to actually do software updates.Alessio [00:17:22]: Just to clarify as well, who is the customer for this? Like, I assume a lot of hardware manufacturers have their own firmware, and I'm sure some of them would just have you write it for them because you're experts. And others would have their own. Like, who pays for this? Who invites you into the house? Is it, is it the end user, or is it, is it the manufacturer?Peter [00:17:41]: Yeah. So let me make an analogy firstly on the on the fragmentation of software. So physical machines today are more akin to the state of the phone market before Android and iOS existed, right? So I worked on Android at Google by the way many years ago, and part of the reason that Larry at Google decided to get into Android was they wanted to run Google products on a bunch of phones, and they bought all of these phones from the industry, and it turned out they had like 50 different operating systems on these phones. And it was virtually impossiblePeter [00:18:17]: for Google to make their app run on all 50 devices equally well. And so the solution was, well, actually what if, what if they created-A really great operating system and made it attractive to all of these phone makers, and that was sort of the genesis for what Android was and why Android existed. It was a way for Google to get their products onto really wide diversity of devices. The state of the physical, industry right now, it's a little bit like that. Like, there's yes, these companies have firmware, but they have so many different operating systems, it's so fragmented, and to actually get a modern AI application to run on these vehicles, you actually, you first have to consolidate the operating system, and so that's, that's why we've done that. And then, your specific question was who are our customers? It's, it's, generally it's the companies that are making these machines.Peter [00:19:06]: And we're, we're, we're selling our technology to them to really simplify the architecture and then enable these AI applications to run on them.Customers, Licensing, and the Better-Together StackSwyx [00:19:13]: How much is reusable across? Like, do you have, like, one OS that is just configured for everything, or is there some more customization that is needed?Peter [00:19:22]: Yeah, highly reusable. So the fundamental technology is quite universal, right? So things that we do have to think about though are, like, chipset support. And so if you're, if you're coding, let's say, an LLM and you have start with an assumption that, “Hey, oh, I'm gonna, I'm gonna use CUDA, and I'm gonna run this, on an NVIDIA chip,” then you don't really have to think about the hardware in that sense. Like, you're just, “Okay, I'm just I'm in the CUDA/NVIDIA ecosystem, and I'm, I'm going to use that.” But the hardware, especially in safety critical systems, it's a lot more diverse. There's not one or one or two players. There's a bunch of different chipsets that we have to support. And so our operating system doesn't just run on, like, the equivalent of X86. It has to, it has to run on a number of different architectures from chips from a bunch of different companies. But again, we've been working on this for a long time now, so we have, we have support for all of those chipsets. And then when you want to then run the AI applications, we can then do that reliably across now a variety of providers.Qasar [00:20:19]: And I think that is, like, heavily inspired by Android, right? Android has a huge suite of testing and it's a reliable operating system that runs on thousands of devices. And we think we can, we can do the same in all these physical moving machines, with the difference that we're really in a safety critical realm. Android isn't.Alessio [00:20:40]: So on Android, I don't need to use Gmail, I can use Superhuman. Like, what about your machinery? Like, can people bring somebody else's automation to it, or is it kinda like all-in-one?Qasar [00:20:50]: You have to use us. No. Yeah. we're If, Yeah. Yeah, it's totally open. Yeah.Peter [00:20:56]: Yeah. our philosophy is that we are a technology company, and so we license our technology to customers to use how they want. And so if a customer wants to If they wanna license our autonomy tech and our operating system, then great, we'll license those. If they just wanna license the operating system and then use different autonomy tech, that's fine also, and we have great documentation andSwyx [00:21:17]: Or if they wanna use developer tooling.Peter [00:21:18]: Yeah, exactly.AI Coding Adoption: Cursor, Claude Code, and the Bimodal EngineerSwyx [00:21:19]: It's, like, a better together if, obviously, if you, if they work together. Is it all C++ I assume is with different compile targets?Peter [00:21:27]: We use a lot of C++.Peter [00:21:28]: Rust is sort of a hot, the new hot kid on the blockPeter [00:21:32]: for a bunch of things as well. But yeah, the lower level you get, especially when you get to real-time constraints, you hit C++ at some point, and at some point maybe you work your way into assembly when needed.Swyx [00:21:44]: Oh, damn.Alessio [00:21:46]: I'm curious about the coding agent adoption, just, like, since you're mentioning more esoteric languages. Like, what's the adoption internally? What have you learned?Peter [00:21:55]: Yeah. We use everything. So Cursor was, I think the hottest tool in the company for a good while. Now Claude Code, I think has taken the reign on that. We have a internal leader, leaderboard that we use just to sort of encourage adoptionPeter [00:22:09]: with-within the company. And yeah, it's, they're phenomenally useful. it's, Honestly, we take inspiration from some of those tools also in how we're adapting some of that mindset of thinking to the physical realm. Like if it's so easy to build an app for this or that thing that lives just on a screen, we can We're taking now a lot of the same ideas and applying that to, “Okay, well, if you wanted a physical machine to do something, how easy can we make that, using our own tooling and platform as well?”Alessio [00:22:40]: Are you changing any of, like, the OS architecture, kinda like the way you expose services to, like, be more AI friendly or?Peter [00:22:48]: Yeah, absolutely. The in the early days of our tools infrastructure work, it was a lot about, You had engineers that were experts in certain topics, but the things that you're dealing with, they're oftentimes more mathematical or more abstract, where actually GUI tools are very useful for certain things. Like as an example, we have a product we call Sensor Studio, which is, it helps you design the sensor suite for your autonomous vehicle, whether, again, it could be a car, it could be a drone, could be a mining equipment, could be a robot. And you place sensors in different places. You There's different, There's a library. You can understand what are the trade-offs that you're making in the design of that system, and that was, like, a very, a very GUI intensive, thing ‘cause it's a little more like a CAD tool in that senseSwyx [00:23:37]: YepPeter [00:23:37]: if you've seen CAD tools. Nowadays, though, right, we expose all of the underlying APIs for that and now using, AI agents, you can actually configure a sensor suite with just text and likely reach a better result than you could've through the GUI in the past, and we're taking that thinking now through the whole product portfolio.Swyx [00:23:57]: Another thing I was thinking about is just in terms of, like, AI, adoption, does it change your hiring at least a little bit, or how do you, how do you sort of manage engineers, differently?Peter [00:24:08]: Yeah. absolutely, it does. we, I think like every company in the Valley right now, are evolving our hiring practicesPeter [00:24:16]: because the skills required to be effective are changing so fast, right? you used to really select for just rote implementation ability and now it is more the AI engineer skill set, right? Where it's like, yeah, how to implement, but actually-Just banging out code is no longer the core job, right? It's, it's actually knowing what questions to ask, knowing how to tie, how to tie together these different AI tools. And so the interviews that we give now I think are way harder than they've ever been.Peter [00:24:46]: But we also allow, right, selective use of AI tools to solve the problems. And I think in that you start to see more of a bimodal distribution of engineers, right? You start to see like wow, there's, there's this subset of people that they really get it. Like they're, they're all in and they've, they've clearly invested the hours needed to learn these tools and how to be effective.Peter [00:25:09]: And then there's sort of the group of people that haven't done that, and that the productivity gap is just enormous. And so we're, we're trying to obviously select for the people that are really into this.Qasar [00:25:20]: I first wrote the my AI engineer piece three years ago, and when I first wrote about it, I was like, “Actually, not everyone should be an AI engineer,” ‘cause I think there's a there's an extremist stance where well, every software is an engineer is an AI engineer. And my actual example of people who should not be adopting AI was embedded systems and operating systems, and database people. Are they adopting AI?Peter [00:25:41]: I think it's the classic bitter lesson, topic, which is the Six months ago I would've said the same thing, but it's, it's becoming super useful for every domain.Qasar [00:25:53]: I'm sure.Peter [00:25:54]: Right? Like,Peter [00:25:56]: there was, I think six months ago, or maybe a year ago, if you tried to use, let's say the latest Claude model for writing shaders, GPU shaders, the results were probably underwhelming. And if you use the latest model now to do that kind of task, you're a little bit blown away, like, “Wow, that actually worked. That's amazing.” And we see the same thing in the embedded realm. No question though, especially when you get into safety critical systems, the human validation isPeter [00:26:25]: is 100% key. Like I You're not gonna trust your life to a an AI written software that's, that's not been very carefully, checked by humans. And so I think now the really the challenge is about that appropriate level of human validation for these safety critical systems.Verifiable Rewards, Evals, and Neural SimulationAlessio [00:26:41]: How do you think about, yeah, touching on the simulation side, I think verifiable reward and reinforcement learning is, like, the hottest thing. What have you done internally to build around that? And like, what gives you What makes you sleep at night? Like, if somebody's like, just web coding something or likeAlessio [00:26:57]: wants to try something new, you have like a good enough system. Because I think the opposite is also true, is like if it's super easy to write anythingAlessio [00:27:04]: then it puts a lot of work on like the verifiableAlessio [00:27:07]: side of it. Like, what does that look like for people?Peter [00:27:10]: Yeah. So verifiability, a broader bucket of like evaluations, right? Like how do you evaluate the results that you're, you're getting? I think this is probably the hardest problem right now, because the As the models get better, it can be harder and harder to find the faults on the system.Peter [00:27:29]: And so like the problem of doing proper eval to find those faults, like that problem also keeps getting harder as the models get better. But it's no less important than it's ever been, right? You still there are still going to be edge cases that are not met and whatnot. And so it's, it's a big area of investment for us. On the reinforcement learning topic, the key thing is there's all these new requirements that come to be in the latest generation of these technologies. So for example, end-to-end is the big thing right now in autonomy and physical AI, which is you can now train these models that can effectively take sensor data in and then put control signals out, and get really good results out of that. But the way that you train and improve those models is really different from the previous generations. And so to do reinforcement learning on an end-to-end model, you now need to actually simulate all the sensor data, right? So then this becomes a we call our, work in this neural simulation, but it'sPeter [00:28:26]: think of it like a hybrid of Gaussian, splatting and diffusion methods, and where you really care about performance. Like performance is everything. If you can't do enough simulation fast enough and cheap enough, you actually can't get results that are worthwhile, in the end. It also gets to a lot of our work in embedded systems, which is like performance critical work, and that performance optimization, performance criticality, it carries over to a lot of the model training work. because, like, the only way to make it affordable is it has to be really fast.Qasar [00:28:58]: I think it's worth a few minutes talking about our own, evolving thoughts on verification and validation withinQasar [00:29:05]: kind of, traditional simulators, which are, you can think of like vehicle dynamics or something like that, which you're just taking textbooks and taking those formulasQasar [00:29:13]: and putting them into software, to like now this neural sim/world model universe. I think that's an interesting topic.Peter [00:29:20]: Yeah. So in more traditional development, right, you oftentimes would have, more black-and-white answers to questions.Peter [00:29:28]: And so the in Europe as an example, there's, a regulatory, system, it's called Euro NCAP. It's the European New Car Assessment Program, and as part of that, the vehicles have to pass a bunch of tests, and those tests actually, include, safety systems. So automatic emergency braking for a child that runs in front of a carPeter [00:29:51]: or let's say an occluded child that runs out and you hit it. And so you have You end up with sort of these binary answers of like, well, did the car under test pass this specific test? And there's a very well-known set of test casesPeter [00:30:05]: that the vehicle has to pass. And that was how the industry worked, let's say, until 10-ish years ago. But what's changed now is with these models, everything is statistics, right? Like you no longer have a black-and-white answer, but it's like, well, how many orders of magnitude or how many nines of reliability can I get in the system, and how can I, how can I prove that to be true? And the big unlock honestly for physical AI as an industry is that these models are just becoming much more reliable. Right? Things like things actually work a lot better. It's like the number of nines you can get out of these systems are now good enough that it actually becomes cost effective to really deploy these things. And so the big shift in, so verification and validation has been from a little bit more of a Again the past it was strictly requirements, and are you meeting or not? And now it's more of a statistical, verification and validation case where it's all about how many nines of reliability and meantime between failures, that sort of thing.Statistical Validation, Regulators, and the Cruise LessonSwyx [00:31:04]: And is the target audience regulators or even the customers are yeah, if you I imagine the customers are bought in, and it's mostly regulators that need to be satisfied.Peter [00:31:15]: We do work with the US government, we do work of course with the European governments and the government of Japan, and the government is not like an AI lab by any means.Peter [00:31:25]: So Swyx [00:31:26]: They just care about the outcome.Peter [00:31:27]: They care about the outcome.Peter [00:31:28]: And so we do education, in that regard, and like so sort of teaching about, “Hey, this is how we think validation should be done, and this is an approach that we think is reasonable,” and how to think about like when is a driverless system actually safe enough to go on the roads and that sort of thing. But I wouldn't say that the government is asking for it. It's like we're more teaching the government in that, in that sense. It's honestly, it's more so for our own, our own comfort, right? Like, we want to build very safe systems, and then of course our customers care deeply about that as well. But in that context we're also typically educating our customers.Qasar [00:32:01]: Yeah. Our first, our first core value is on round safety. So I think we can't underline enough that, us also verifying and validating that the systems that we're deploying are safe to us is probably as important as, like, some regulator or a customer saying,Swyx [00:32:19]: Of course. Okay. Yeah.Swyx [00:32:20]: You have to satisfy yourselves.Peter [00:32:22]: As I say, as a whole across the world, regulation oftentimes it's like a almost lowest common denominator. But like, you really have to substantially exceed what the regulators are expecting to make good products.Swyx [00:32:33]: Yeah. One thing I often talk about, I think and I try to make this relatable to the audience also, is Cruise, where they had an accident that basically ended the company. I wonder if people overreact to single incidents, because incidents are going to happen regardless, right? ‘Cause it's a statistical thing, but as long I don't know if regulators understand that, you cannot extrapolate from a single incident, but we do because that's all we have to go on. And your sample sizes are necessarily gonna be lower than, I don't knowSwyx [00:33:00]: consumer driving.Qasar [00:33:01]: Yeah. I think the Cruise example wasn't a technology failure. there was The real, compounding issue there was just how did the company talk to the regulators and what was their kind of behavior, and I think that became more of the issue. If you look,Peter [00:33:19]: It isn't It definitely was a technology failure, but it was made much worse by theSwyx [00:33:23]: Put the car back on the woman.Qasar [00:33:25]: Yeah. And let me put it another way. There is a version where Cruise still exists.Swyx [00:33:29]: right. Right.Qasar [00:33:30]: Right. It'sSwyx [00:33:30]: It was like the last strawQasar [00:33:31]: ItSwyx [00:33:31]: in like a long chain ofSwyx [00:33:33]: like issues.Qasar [00:33:33]: So do you feel like ATG had that horrific accident or someone actually dying, because, that was a homeless person crossing the street? So yeah, I think we can't understate enough that ultimately, like, statistical validation of something, that's one part of it, but it's not the only part of it. Like, consumer and let's say, mainstream adoption of these technologies is also gonna be part of that conversation. I think companies like Waymo are doing a lot of service positively to the industry in the sense of they're, they're setting a high benchmark and they're showing, kind of in a very responsible way how to, how to deal with these. There have been Waymo incidences as well. They've just not been as significant as the Cruise one that you mentioned. But yeah, so I think you'll just continue to see that. I think probably the long term question is really gonna be, again, around Like it is very clear humans are way worse drivers statistically.Qasar [00:34:29]: Like, there's no, there's no debate. And so at what point But we're emotional animals.Swyx [00:34:34]: Yeah. So my thing is, like, we have to get to a point as a society where we accept horrific accidents that would never happen by a human because statistically we understand that it is safer overall. In the same way that planes, they're safer, than I think they're the safest mode of transport that we have.Qasar [00:34:50]: Yeah. it's more dangerous to drive to the airport than it is to get on a flight.Qasar [00:34:53]: So if you're everQasar [00:34:54]: if you're ever getting nervous about getting on a plane, just think “I just gotta get to the airport.”Swyx [00:34:58]: Yes, we're flying.Qasar [00:34:59]: If I get to the airportQasar [00:35:00]: I'll be good.Swyx [00:35:00]: But then it's, planes also concentrate the tail risk if planesQasar [00:35:03]: Yeah. AndPeter [00:35:04]: And I was, I don't think we honestly have to worry about there ever being, accidents from these systems that are like much worse than what humans would cause, ‘cause humans do terrible things.Peter [00:35:14]: Like, people fall asleep at the wheel all the time.Swyx [00:35:16]: I have.Swyx [00:35:17]: Like, I'll call, I've been a drowsy driver.Peter [00:35:19]: Kinda drunk drivers, and that'sPeter [00:35:20]: that's the extreme end of the example. But these AI systems, you have redundancies, you have fallbacks. Like, there's many things have to go wrong for there to actually be a something catastrophic because there's, there's so many, fallbacks that these systems have.Alessio [00:35:36]: your simulation is like so vast because there's so many use cases. What are, like, maybe things that worked in a simulation and then you put it out and it's like, “F**k, this isAlessio [00:35:45]: this just did not work at all?”Peter [00:35:47]: Yes.Alessio [00:35:47]: IsPeter [00:35:47]: That's maybe a bit of a misconception, about simulation there. So let me go a little bit, more technical on this. So at first go, no simulation is going to represent the real world. There's always a process of this, sim to real matchingPeter [00:36:02]: where you actually, you need the real world feedback to basically feed into the parameters that are being used in the simulator, and you have to do that, it's like this validation flow, a number of times until you can get some confidence that, like I think the simulator is now accurately representingPeter [00:36:19]: what's gonna happen in the real world. Now, if you have a situation where you've done that full validation and you thought that it was accurate and then there's something different, those are much trickier cases, and that's, that absolutely can happen, but really I think the validation process is a really important part. You can never skip the simulation validation process, like where you're actually ensuring that, hey, the actual, my sim to real gap here is small enough that I can trust these simulation results. And there's, there's so many fun things that you can do when you get into it. Like, I'll, I'll give one fun example that came up recently is like in these humanoid robotics, systemsOverheating actuators is a real problem, right? So obviously phenomenal demos. IPeter [00:37:01]: The most amazingAlessio [00:37:02]: For 10 minutes.Peter [00:37:03]: The most amazing I can get. I love, I love watching robots do acrobatics like everybody but the these systems actually overheat, right? If, like, And one of the ways you can use simulation though is you can actually have that, the temperature of those actuators be one of the parameters that's representedPeter [00:37:18]: in the simulation. And if you're doing reinforcement learning over a certain task, then the robot can actually adjust its motions in the simulation to account for the fact that, oh, it knows that as it's moving, it's actually beginning to overheat this motor. But if you didn't have that parameter of, let's say, the heat of that motor represented in the simulation initially, then your RL policy might It will disregard that. And now you run that on the robot and the robot will overheat and fail.Alessio [00:37:43]: I guess the question is, like, how do you have all of these parameters taken care of while also understanding the deployment environment? Like, temperature is like a great example, right? WellAlessio [00:37:53]: why did you make my robot worse when it runs in like a freezer?Alessio [00:37:57]: So it actually shouldn't worry about that. it's like, yeah, how do you design these simulations?Peter [00:38:02]: This is honestly the This is what makes simulation so hard, right? it's because you Simulation is fundamentally about you're trying to optimize the development of a system, right? Like, how can I build this system faster and better and cheaper and what are all the levers that I have to actually accomplish that? And because simulation's just a software program, you can, you can change it a lot more easily than you can hardware systems. And then what's particularly awesome about the let's say, world models and using that as a part of simulation is now the simulation doesn't just scale with, let's say, adding new math equations inPeter [00:38:36]: but we can actually scale the simulation environment now with additional real world data and that also unlocks a whole new field of robotics.Qasar [00:38:46]: There is a meniscus line where you cross where still doing real world testing is better. there's, in this, sim-to-real gap, you can reproduce reality at exceedingly expensive costs and this So nothing is free. So really you have to you're finding that line where you're getting great performance, you're getting great feedback, whether it's on the training side or on the eval side, but it's way cheaper than doing it in the real world. At some point it, that doesn't make sense. And so even, from our earliest days in autonomy, our view was you're still gonna do real world testing. You There's, there's not, there's not this, magical land where you're not gonna do that. And maybe even like a more nuanced version of this in like traditional software development is, most of your testing for software in a vehicle, 95% of that can be like traditional CI/CD kind of, flows that you would have in traditional web development. But once you have Now you, let's say you have a truck. Well, you can do like 4% of those in like a rig which has all the components, the electrical and electronics of a truck, but doesn't have, it doesn't have the tires and it doesn't have the And then you have the 1%, which is actually the vehicle. There's something There's a similar analogy in terms of using simulation for intelligent systems. You can do a lot in a simulator, but in using world models, but ultimately it's, it's physical AI. So you're gonna deploy it on physical machines andQasar [00:40:17]: the freezer example comes to, comes to light.Alessio [00:40:20]: The world model thing has been to me the hardest thing toAlessio [00:40:22]: wrap my head around. Like we have Faith Eliyon on the podcast.World Models, Hydroplaning, and Cause-Effect LearningQasar [00:40:25]: We've been doing a small series with like another Intuition company, General Intuition as well.Qasar [00:40:31]: yeah, and I mean, lots of, lots of coverage on NeRFs and yes.Alessio [00:40:34]: Yeah. It feels like we talk with about, the heliocentric system, right? It's like in a world model, if you just feed visual data, the model might learn that the sun spins around the Earth. It makes sense, right? And it's like, well, not really. And I think what are like some of these other things that like hydroplaning is one thing I think about, is like can a world model understand hydroplaning and like what amount of water like causes it to happen? And it's like, yeah, to me it's like I don't understand how you guys do it. I guess it's like the real thing is like when you're doing both cars and the highway in Japan versus the excavator in a mine in,Qasar [00:41:13]: ArizonaAlessio [00:41:13]: wherever you're Arizona, wherever you're deploying them.Alessio [00:41:15]: How much of it are you relying on the world models to like generate the simulations for you and then try and close the gap after versus like giving the world models as a tool to your engineers to like curate the simulations if that makes sense?Peter [00:41:28]: Yeah, totally. So yeah, I can say at a pure engineering level, I think if you're hoping to do real world deploys and you're purely relying on a world model approach, you probably won't get to something that works, before you go bankrupt. So there is just a very practical mindset of like, world models are amazing and they're extremely useful for a lot of use cases, but there are a lot of other things that you need to do to actually get something started and something deployed and working. most fundamentally, world models are all about It's understanding the world, but also understanding what's going to happen. It's like the cause-effect relationship.Peter [00:42:01]: Right? And so like it, right, if you have a take some sort of construction tool, and that construction tool is gonna be doing some work on the Earth in some way, it's gonna be moving earth, the world model needs to understand that cause-effect relationship. Like, okay, when I, when I take this material from here and put it over there and now I have things that are over here and not over there anymore and that cause-effect, relationship. data obviously is a is a big problem. The hydroplaningPeter [00:42:26]: one is actually a really great example because it's actually quite non-obvious sometimes. Right? It's like, well, it's, it's raining and well this road, has, let's say the appropriate curvature to it so the water is running off the road and cars are driving faster here and then you approach a road that's very flat and water is now puddling on that road and all of a sudden cars are driving slower because when they were driving faster they were starting to lose control. And there are a lot of visual nuance, very nuanced visual cues in the scene and so I do think in the world model concept there's a good chance that the model actually would learn that you should just drive slower when these visual cues exist, and that's obviously the beautiful-The beauty of, these kinds of models where they just, they learn these non-obvious things.Swyx [00:43:14]: It doesn't need to know about hydroplaning to know that it needs to drive slower.Peter [00:43:17]: Yes.Swyx [00:43:17]: I guess it's Yeah. I wanna ask questions about, also deploying models. I presume, like, you use a lot of these world models for training data and simulation, but what about deploying it onto the systems in production? Presumably you have you have, like, GPUs on deviceOnboard vs. Offboard: Latency, Embedded ML, and DistillationSwyx [00:43:36]: but they're I keep saying on device. What's the what's the right term for that?Peter [00:43:40]: On machine.Swyx [00:43:41]: On machine.Peter [00:43:41]: Or embedded, yeah.Swyx [00:43:42]: Yeah. What is the embedded world like? because for people who are not used to that world, this is very alien.Peter [00:43:49]: Yeah. So it's actually We call it onboard and off board.Peter [00:43:52]: So like, onboard software and off board software.Peter [00:43:54]: And the great thing about off board software is you don't have to care about time, and you can run really large models, right? So you can, you can say, “Well, this model, I don't care if it takes one second for it to give me a result or 10 seconds for it to give me a result, because we have time.” And the models can be really big, and they can run, in a data center or on a on a huge GPU and you can obviously have distribute to compute, et cetera. But onboard you don't have any of those benefits. You're like, “Well, I need I have this many milliseconds where I need an answer from this model.” And so a lot more of the energy then is about, think of it more like distillation and it's like truly efficiency and like, literally every fraction of a millisecond counts. And you can't have a situation where the model takes too long because then the vehicle can't actually function.Peter [00:44:42]: And so you can, you can still use a lot of the same techniques, and the models themselves you can think of as like a derivative of larger models that you can run offline, and then you're, you're trying to just get a model that is still performs really well but it's, it's a it's smaller, small enough version that you can then run on this embedded system where you care about latency and power.Qasar [00:45:03]: Yeah. And I think like, the broader point I think which, maybe is not obvious but it's worth saying is in physical AI world, we're not really constrained right now by, like, the intelligence of the models. It's actually what Peter's talking about, it's actually deploying them inSwyx [00:45:19]: The hardware they give you.Qasar [00:45:21]: Yeah. On the hardware you give you.Qasar [00:45:22]: And so And there's just a reality is of safety critical systems. So those end up being the your limiting factorsQasar [00:45:29]: rather than, let's say, a limiting factor for, a foundation model companyQasar [00:45:34]: is gonna be just capital maybe or researchers.Qasar [00:45:38]: So we're, we're in that way dealing with, for us as people who kind of come in that realm with like a very interesting Those constraints force creativity.Swyx [00:45:47]: And I imagine, nobody was deploying or giving you the hardware for transformers back in 2018, whatever, but now they are. What's the evolution like? just peel back the curtains a little bit.Peter [00:45:59]: Yeah. Transformers first off, I think the paper was originally published in 2017.Swyx [00:46:02]: 2017.Swyx [00:46:02]: So there's no time.Peter [00:46:04]: And ISwyx [00:46:05]: But I'm just saying I guess I'm saying, like, embedded ML systems usually, like, a lot less parameters, a lot less compute, and now, like, orders of magnitude more.Peter [00:46:14]: Yeah. absolutely. what I was gonna say though was I think in the in the original paper in 2017, maybe it's in the last paragraph, somewhere in the paper they talk about, like, “Oh, by the way, this technique might be useful for, like, images and videos as well.”Peter [00:46:30]: These last subjects.Peter [00:46:31]: And it took a few years for that impact to really hit. But like, now, we're seeing transformers are everywhere.Swyx [00:46:39]: Yeah. Vision transformers.Peter [00:46:40]: And then then the compute just keeps getting better and better. But you do have this fundamental trade-off, right? It's like you have power, you have cost, and performance and like, getting the right, getting the right mix of those things in an embedded package that can also be, like, shaken and baked in all thePeter [00:47:00]: conditions that these things have to have to operate in. But yeah, I think that they're only going to keep getting better and so we also try to plan our strategy understanding that, we know the rate of improvements of these systems.Swyx [00:47:11]: Yeah. So like, Google just released the Gemma 2B modelSwyx [00:47:15]: that effective 2B model. Is that useful to you guys or is that too big?Peter [00:47:18]: You can run that model on an embedded system, definitely.Peter [00:47:21]: the So yes, it's, it's useful in that regard. The bigger question is, like, what do you use it for in an embedded system? Like, you actually need to customize it quite a bit to make it useful for something. But yeah, you could run a two billion parameter model, definitely.Swyx [00:47:35]: It also interesting, like, what percent is a custom ML model that only does that thing versus a generalist LLMSwyx [00:47:41]: which probably is not that useful actually for your context.Peter [00:47:46]: Like, you, like, you can imagine different use cases, right?Peter [00:47:48]: So theSwyx [00:47:49]: The voice stuff, yes.Peter [00:47:49]: Yeah, the voice test. Totally, yes.Peter [00:47:51]: So for the actual, autonomy elements, that's 100% in-house. We do every bit of that, the data simulation, the model, everything. But when you get into the more generic use cases like voice or voice assistant kind of thing, that's where these more generalist models like Gemma actually can be quite, can be quite useful.Swyx [00:48:09]: Yeah. And then there's also obviously a trade-off between, like, what percent must you do on machine, versus just call home.Peter [00:48:16]: Yeah. It's all about latency.Swyx [00:48:17]: Latency.Peter [00:48:17]: It's all about latency. Yeah.Swyx [00:48:18]: Yeah. Well, like, I think actually in a lot of contexts, especially in the US, you can just have a connection to the web.Qasar [00:48:26]: Yeah. I think though most of our universe is everything has to be fairly, embedded and local because just the nature of Even in the US there's a lot of likeSwyx [00:48:39]: PatchinessQasar [00:48:40]: don't haveQasar [00:48:41]: have coverage, right? And if you look at, like, the old world of autonomy within mining, which is, like, long before transformers and kind of, neural networks, in the like CNN and kind of a universe, they were really just hand-coded, systems. They were just like, this machine is gonna run to that place with thisPeter [00:49:03]: That was our GPS, like very accurate GPS.Qasar [00:49:05]: Yeah. And so that worked, and that worked for 20 years, so why would we actually need to use transformers or kind of more modern end-to-end systems? Mainly because you can only really run a path and run backwards. That provided a lot of value, but m-Not as much as you get when the machine is actually intelligent. It's, it's seeing, it's perceiving, it's acting in a dynamic world.Alessio [00:49:28]: I looked up RTK, real-time kinematic, one to two-centimeter accuracy.Qasar [00:49:32]: Yeah. Fantastic. But the and fantastic in faraway lands where there's not gonna be cell phone coverage.Peter [00:49:39]: Yeah, so it's widely used on the legacy mining and agricultural autonomy systems today. So like, for example, a combine that can be precise within one or two centimeters as it's driving down the field, they use RTK.Qasar [00:49:53]: Yes.Peter [00:49:53]: But it's, it's expensive.Qasar [00:49:54]: Yeah. And it's, it's, it's autonomy, but it's not intelligent in the way that I think all of usQasar [00:49:58]: if in twenty-six we'd be talking about intelligence.Alessio [00:50:00]: In one of your blog posts, you mentioned research on large scale transformers that are similar to those doing modern generative AI. What are, like, the big differences other than, “You're absolutely right. I should steer the car, so you probably wanna remove that?”Peter [00:50:14]: We have a diversified bet strategy internally, and the reason we've done that is because we operate in now a bunch of industries, a bunch of geographies, and each of the approaches has, obviously a different risk to them.Peter [00:50:27]: And so like, we're not going to put all of our eggs in a single basket for a single approach because that approach may no

99% of all US businesses and almost 46% of American employees are, or work for, a small business. Although a small business is defined as having less than 500 employees, American small businesses are responsible for over 88% of net job growth. That means that America's economy, and the world's economy, rest on the backs of small businesses. The Small Business Administration plays a critical role in the success of small businesses; including those owned and operated by American Veterans. From business planning, strategy design, funding and specialty certification programs the SBA is one of the primary pillars creating and supporting economic impact.In this episode, Fran Racioppi sat down with Bill Briggs, Deputy Administrator of the U.S. Small Business Administration, to break down the SBA's 3C's and a D: Capital, Counseling, Contracting and Disaster. Deputy Administrator Briggs explained the real challenges business owners face, especially around cash flow, capital access, and navigating competitive marketplaces. He shared the history of the SBA and its grounding in the Small Business Act of 1953, when the post war period identified that small businesses are not only important to the global economy, but they are crucial to America's national defense. 200,000 service members transition each year from the military into the civilian sector. Some will start businesses as entrepreneurs. Others will enter the workforce. All will need counseling, support and a system designed to give Veterans access to opportunity and the chance to succeed post service. Finally, we address how the SBA is improving accountability, cracking down on fraud, and ensuring programs are delivering real results for those they are designed to support.Highlights0:00 Introduction2:16 Welcome to the Jedburgh Podcast4:01 Small biz is big biz4:57 SBA Team8:13 Access to Capital11:58 Counseling Resources16:14 Access to Contracts22:01 Disaster Loans25:33 The Formation of the SBA27:16 Made in America Loans29:54 Working Families Tax Cut Bill33:10 Stopping Fraud35:51 Importance of Service39:08 Boots to Business52:02 Daily HabitsQuotes“We're taking it to the next level in terms of right sizing, streamlining, and improving the overall performance of the agency because the mission is so important.”“Access to capital is one of the top three issues that are always facing small businesses.”“What we're trying to do under this administrator and this President is trying to improve our systems to scale and deploy more capital effectively with our lending partners and investors.”“I always say to people you have to have that education before you walk in to try to get that loan.”“Your job is to compete to solve the mission, not to say ‘I'm a certification, I deserve something.'”“Having a competitive, innovative national small business ecosystem is not only part of our economic security but our national security.”“We're trying to bring back American manufacturing .”“Our priorities are manufacturing, critical technology, and food production and technology.”“Our economic agenda is centered on fair trade, tax cuts, deregulation, and energy dominance.”“There's something for everyone in the Working Families Tax Cut Bill.”“We have a zero tolerance policy for fraud.”“The day you start your business is not the day you get paid.”“We're overhauling how we deliver our boots to business.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

Don't experiment on your own revenue with broken game mechanics. Get our guide "Core Drives in the Wild" to learn how to apply real behavioral science to your product: professorgame.com/WildCD Most companies treat user churn as a data problem, but looking at "where" someone leaves doesn't explain "why" they lost interest. We break down the "Engagement Leaks," a phenomenon where record-breaking marketing spend fails to fix a product that is effectively a sieve for users. By analyzing the high-touch onboarding of Superhuman, the "novelty hangover" of Robinhood's digital confetti, and the legendary community design of Harley-Davidson, this episode reveals how to use the Octalysis Framework to plug leaks in different stages of the user journey. A masterclass in transitioning from a product people merely start to one they actually stay with. Rob Alvarez is Head of Engagement Strategy, Europe at The Octalysis Group (TOG), a leading gamification and behavioral design consultancy. A globally recognized gamification strategist and TEDx speaker, he founded and hosts Professor Game, the #1 gamification podcast, and has interviewed hundreds of global experts. He designs evidence-based engagement systems that drive motivation, loyalty, and results, and teaches LEGO® SERIOUS PLAY® and gamification at top institutions including IE Business School, EFMD, and EBS University across Europe, the Americas, and Asia.   Links to episode mentions: Superhuman Robinhood Harley Owners Group (H.O.G.) The Octalysis Group   Lets's do stuff together! Core Drives in the Wild: Professor Game Guide Let's chat about your gamification project YouTube LinkedIn Instagram Facebook Start Your Community on Skool for Free Ask a question

Leave an Amazon Rating or Review for my New York Times Bestselling book, Make Money Easy! Check out the full episode: https://lewishowes.com/podcast/become-superhuman-with-your-potential-with-colin-obrady/ Colin O'Brady, known for his incredible feats of endurance, shares his wisdom on achieving seemingly impossible goals. Colin holds the world record for the fastest ever solo trek across Antarctica, in addition to several other world records. He's an elite endurance athlete at the top of his game, but he knows that the most important muscle is actually your brain. Sign up for the Greatness newsletter: http://www.greatness.com/newsletter Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Service is an honor and a burden carried by more than just those who don the Green Beret. Service is borne by the family that stands in the shadows every step of the way. Through training, deployments, uncertainty, the highest highs and the lowest lows, it's the family that waits for their Green Beret to return. From the 2nd Annual Stars and Stripes Classic, Fran Racioppi sat down with Bianca Baldwin and Fran Wesseling, the spouse and mother of Major Darren Baldwin; a Green Beret who came home from combat, but was never the same. Darren's journey began at the United States Military Academy, where he played lacrosse and built the foundation of discipline, teamwork, and commitment that would carry him into Special Forces. During a deployment, Darren was forced to return home early due to what initially seemed like minor health issues. Further evaluation revealed lesions on his brain, marking the beginning of a long and uncertain fight. Diagnosed with Progressive Traumatic Brain Injury, Bianca and Fran answered a family's hardest call to service. They shared with me the critical role a family plays in the success of a Green Beret, why strength is important, and how caregiving gives hope to the wounded and their loved ones. Darren passed away from his combat-related illness, and to honor his life, Bianca and Fran carry forward his legacy through the MAJ(R) Darren Baldwin Silver Star Families Support Fund and through the support of the Green Beret Foundation, ensuring that other families will never fight alone.This episode is about the service of a family during, and after that of their Green Beret. HIGHLIGHTS0:00 Introduction1:51 Welcome to the Stars & Stripes Classic3:38 Who was MAJ Darren Baldwin10:14 Silver Star Families Fund15:02 Progressive Traumatic Brain Injury22:20 Resources AvailableQUOTES“Both of my boys slept with a lacrosse stick.”“He had a dedication and grit that goes beyond most.”“Ultimately deeply grateful that his legacy and memory lives on.”“It was like trying to make a right of a wrong.”“That's kind of how our story started and my story as a caregiver.”“I was always his wife but became his 24/7 caregiver.”“The vast majority of people, including the military, don't even know what Silver Star families are.”“The fund provides all kinds of medical equipment and new technologies.”“It's difficult and thankless work to be a caregiver.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

This week's stories: *Bartonella Hides in Cat Scratches — and It Might Be Why You Feel Like Garbage A stealth bacterial infection transmitted by everyday cat scratches and flea dirt has been quietly linked to chronic fatigue, brain fog, and neurological symptoms for decades. Dave breaks down how Bartonella slips past standard testing, why it's almost never on a conventional doctor's radar, and the specific PCR protocol you need to actually find it. Sources: https://pubmed.ncbi.nlm.nih.gov/ *High Tyrosine Levels May Be Cutting Years Off Men's Lives A Mendelian randomization study of 270,000 UK Biobank participants found that elevated tyrosine is causally linked to nearly a full year of lost lifespan in men — with zero effect in women. The culprit appears to be an inflammatory oxidation pathway that men metabolize very differently. Dave examines what this means for every guy stacking L-tyrosine nootropics or eating high-protein keto. Sources: https://pubmed.ncbi.nlm.nih.gov/41045493/ https://www.aging-us.com/news-room/high-tyrosine-levels-linked-to-shorter-lifespan-in-men https://www.usnews.com/news/health-news/articles/2026-02-27/study-suggests-one-common-amino-acid-may-affect-how-long-men-live *Blue Light Blocking Contact Lenses Are a Legitimate Vision Upgrade ALTIUS Vision's tinted contact lenses aren't just blue light filters — they cut chromatic aberration by 53% and improve motion tracking and contrast sensitivity in ways that software filters simply can't replicate. Dave covers the mechanism, who benefits most (screen workers, TBI recovery, gamers), and how to find a provider. Sources: https://altiusvision.com/chromatic-aberration/ https://altiusvision.com/science-of-altius/ https://www.westvalleyvision.com/-altius--performance-tinted-contact-lenses *Taurine Plus B Vitamins Actually Moves the Needle on Motivation A randomized crossover trial found that a daily stack of taurine, B6, folate, and B12 sustained effort-reward motivation and cut cognitive lapses significantly compared to placebo — and the mechanism runs through glutathione production in brain astrocytes. Dave breaks down why this combo works when either ingredient alone doesn't. Sources: https://pubmed.ncbi.nlm.nih.gov/41889717/ https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2026.1711478/full https://www.nutraingredients.com/Article/2026/03/23/taurine-and-b-vitamins-bost-motivation-and-focus/ *30 Seconds of Smelling Flowers Resets Your Nervous System Research out of the Monell Chemical Senses Center confirms what your grandmother knew: a slow, deep floral inhale measurably lowers heart rate and activates the parasympathetic nervous system — and it works because olfaction bypasses the cortex entirely and hits the limbic system directly. Dave makes the case for building a daily scent ritual. Sources: https://time.com/ https://www.southtabor.com/healthy-living-tip-stop-and-smell-the-flowers/ This episode is designed for biohackers, longevity seekers, and high-performance listeners who want mechanism-level clarity on infection-driven cognitive decline, amino acid optimization, sensory performance, and evidence-based supplementation. Host Dave Asprey connects emerging clinical research, Mendelian randomization data, and real-world protocols into actionable frameworks for extending healthspan and sharpening performance. New episodes every Tuesday, Thursday, Friday, and Sunday. Keywords: Bartonella cat scratch infection, Bartonella brain fog chronic fatigue, stealth bacterial infection biohacking, tyrosine lifespan men, L-tyrosine risk men longevity, Mendelian randomization amino acid aging, blue light blocking contacts, ALTIUS vision chromatic aberration, performance contact lenses TBI, taurine B vitamins motivation RCT, taurine folate brain health, glutathione astrocytes focus, smelling flowers heart rate stress, olfaction parasympathetic nervous system, floral scent limbic system, biohacking news, longevity research 2026 Thank you to our sponsors! - GOT MOLD? | Go to http://gotmold.com/shop and use DAVE10 to save 10% and see what's in your air. - MASA Chips | Go to https://www.masachips.com/DAVEASPREY and use code DAVEASPREY for 25% off your first order. - iRestore | Grow thicker, healthier hair back naturally. Use code DAVE at irestore.com. Resources: • Get My 2026 Clean Nicotine Roadmap | Enroll for free at https://daveasprey.com/2026-clean-nicotine-roadmap/ • Get My 2026 Biohacking Trends Report: https://daveasprey.com/2026-biohacking-trends-report/ • Dave Asprey's Latest News | Go to https://daveasprey.com/ to join Inside Track today. • Danger Coffee: https://dangercoffee.com/discount/dave15 • My Daily Supplements: SuppGrade Labs (15% Off) • Favorite Blue Light Blocking Glasses: TrueDark (15% Off) • Dave Asprey's BEYOND Conference: https://beyondconference.com • Dave Asprey's New Book – Heavily Meditated: https://daveasprey.com/heavily-meditated • Join My Substack (Live Access To Podcast Recordings): https://substack.daveasprey.com/ • Upgrade Labs: https://upgradelabs.com Timestamps: 00:00 – Intro 00:37 – Bartonella & Cat Scratch Disease 02:06 – Tyrosine & Lifespan in Men 03:37 – Tinted Contacts & Visual Processing 05:56 – Taurine & Motivation 07:25 – Floral Scent & Nervous System Reset See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of The Ross Simmonds Show, Ross breaks down how he built a quarter-million-dollar solo consulting business before 30 and how he would engineer that same growth today as a fractional CMO in the AI era. From personal brand foundations to referral flywheels to public speaking as a client acquisition engine, this is a tactical, no-excuses blueprint for building authority and pipeline as a one-person growth operation. Key Takeaways and Insights: 1.From Basement to $270K: The Origin Story -Ross built a quarter-million-dollar solo business before 30 with no elite network and no big-city advantage. Just reps, value creation, and commitment to the long game. -Underdogs win when they stop waiting for permission and start stacking consistent execution. 2.What a Fractional CMO Actually Does -A fractional CMO provides strategic marketing leadership across brand, messaging, content, search, and growth without the full-time cost. Multiple companies. Real equity upside. -It is one of the highest-leverage positions in the market right now for marketers who own outcomes, not just tasks. 3.Personal Brand Is the Foundation -If someone Googles you today, what shows up? Buy your domain. Control your narrative. Publish content aligned to your niche and your ideal client profile. -Your name is an asset. Treat it like one or someone else will define it for you. 4.Consistency Beats Excuses in the AI Era -AI removes friction. It does not replace strategy. If you have no clients and you are not posting daily, that is the problem. -Visibility is engineered through repurposing content across LinkedIn, X, Threads, YouTube, and podcasts. Not hoped for. 5.Build Leverage with Talent and AI -Combine AI systems with high-level human talent. Use tools like Claude, ChatGPT, Fathom, and Superhuman to increase capacity without adding headcount. -Hire globally. Skill beats geography. Layer systems and people and you get agency-level output from a solo operation. 6.Diversify Revenue Without Destroying Focus -Courses, speaking, e-commerce, consulting — multiple income streams are real. But side quests can build skills or kill focus depending on how you sequence them. -Depth compounds faster than scattered effort. Focus accelerates revenue growth. 7.Referral Flywheels as Passive Leverage -Do great work, earn inbound referrals, and build a referral program that earns without direct delivery. Partner with agencies and specialists to expand capability without expanding overhead. -Compounding trust beats cold outreach every time. 8.Public Speaking as a Client Acquisition Engine -Speaking landed Ross publicly traded clients. Reps build confidence. Confidence builds pipeline. Add value on stage and the rest follows. -Most people fear judgment. The reality: few remember you after two hours. Get on stage anyway. 9.Ignore Hype Cycles. Play the Long Game. -"SEO is dead" is a recurring headline. It has been wrong every time. Trends rotate. Fundamentals compound. -Decades of focused reps create unfair advantage. AI matters. Shiny objects do not. 10.Focus Is a Competitive Advantage -Stop doom-scrolling. Start building. Do not argue with trolls. Create instead. -Protect your mindset like you protect revenue. The long game rewards discipline above everything else. Resources & Tools:

Send us Fan MailPeaches, Trent, and Aaron sit down with Doug—and yeah, this one pokes some egos.Doug breaks down the truth about Army Special Forces, the Guard vs Active Duty debate, and why a lot of dudes are lying to themselves about what actually matters. From getting bullied on old-school forums to building a career in Special Forces, Doug lays it out: most of what people think about the pipeline, the lifestyle, and even “elite performance” is either misunderstood or straight-up wrong.They dive into culture differences between AFSOC and Army SOF, the reality of mentorship (hint: it wasn't always pretty), and why today's generation might actually be better than the one that came before it—if leaders stop being lazy.And then Doug drops the hammer: overtraining is dumb, ego will wreck you, and the pipeline isn't impossible—you're just making it harder in your own head.If you're chasing this life, stop romanticizing it. Start preparing like it matters.⏱️ Timestamps: 00:00 Doug Takes Over the Podcast (Immediately) 02:30 Guard vs Active Duty—The Real Truth 05:00 Why He Joined SF (Not What You Expect) 08:00 Getting Humbled in Basic Training 12:00 Army vs AFSOC Culture Differences 16:00 Losing a Pistol in Combat… Seriously 20:00 Why Mentorship Actually Matters 24:30 Soft Guys vs “Influencers” Debate 29:00 Building Softlete & Brand Reality 34:00 The Next Generation—Better or Worse? 40:00 Intellectual Decline vs Physical Readiness 46:00 Leadership Failure vs Blaming “Kids” 52:00 Stop Overtraining—You're Doing It Wrong 57:00 The Pipeline Isn't Superhuman 01:02:00 Final Advice—It's All in Your Head

263: I sat down with Callan Faulkner to talk about what's actually working with AI right now and how it's changing the way we build and run businesses.(Show Notes: REtipster.com/263)A year ago, AI felt like a cool tool. Today, it's becoming the operating system behind everything. In this conversation, we break down how AI agents, automation, and custom-trained systems are replacing manual work and unlocking massive leverage.We also talk about what's overhyped, what still requires human judgment, and how real estate investors (especially land investors) can start using AI to gain a serious edge.If you're trying to scale your business, free up time, or just understand where things are going, this is a conversation you don't want to miss.

Cars aren't just a mode of transportation. They're a passion. An image. A lifestyle. For many families, they are the bond that brings together father and son. For Frank Viola, cars are the legacy of his son, Green Beret SSG Alex Viola. Alex graduated as a Green Beret in 2011 and then went on to get his Combat Dive Certification. In September 2013, his team deployed to Afghanistan as a part of Operation Enduring Freedom. On November 17, 2013 Alex lost his life to an Improvised Explosive Device (IED) while on dismounted patrol.After the loss of their son, Frank and his family faced the unimaginable challenge of how to move forward. The answer came from something Alex loved deeply: cars. Alex was a true car guy, and restoring vehicles with his dad was one of the ways they spent time together.What began as a simple idea to honor Alex's memory turned into the SSG Alex Viola Memorial Car Show. The first event was held in freezing weather with modest expectations, but the community showed up, raising twenty thousand dollars that first year alone.Today the event has grown into something far greater than anyone imagined. Nearly four hundred cars fill the lot each year, and the show has raised nearly seven hundred thousand dollars to support charitable causes, including the families of Green Berets through the Green Beret Foundation.Host Fran Racioppi sits down with Frank Viola to share how this fundraiser is more than impressive horsepower and jaw-dropping donations. It's a powerful story of resilience, community, and how one family's determination not only honors a fallen hero but has also remarkably reunited their own distant family members and created a new, unbreakable bond with Alex's former Green Beret teammates.Highlights0:00 Introduction1:57 Welcome to the Jedburgh Podcast2:22 Who was SSG Alex Viola?6:11 Why a Car Show?10:05 How loss brought the family together12:34 Alex's Team16:03 The 2025 Show17:02 Working with the Foundations18:36 Advice for Future Green BeretsQuotes“Alex was a father's dream of a son.”“His whole thing was to be out there in the ditches with the guys.”“Alex was a car guy.”“In a million years, we never expected anything like it.”“We have a goal of reaching $1,000,000 in donations.”“There's been some of my cousins that I've never met, but because of this, now we're really close.”“They're like our own kids.”“Losing Alex was probably the worst thing that could ever happen to any parent.”“It's just been a win win all the way around.”“They know we're always going to do the right thing.”“The whole theme of both organizations is supporting the families of fallen and wounded warriors' families.”“I don't think that anyone can just become a Green Beret. You have to be a special kind of person.”“It's either you have it or you don't.”The Jedburgh Podcast is brought to you by OneBrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

Amanda Kahlow raised $30 million to build AI sales agents that improve the buying experience. As the founder of 1mind and previously 6sense, she sits at the forefront of modern go to market strategy. In this episode, Sam Jacobs, AJ Bruno, and Asad Zaman sit down with Amanda to discuss the reality of AI in the sales motion; she explains how Superhumans (1mind's AI Agents) handle everything from top of funnel enterprise pipeline generation to acting as sales engineers on live demos. The conversation covers the technical hurdles of building high performing AI agents, why she believes buyers will soon demand to interact with AI over human sellers, and what revenue leaders must do to prepare their teams for a radically different future. Key Takeaways: According to Amanda, the speed and accuracy of application specific AI will soon eclipse traditional human selling, as Amanda Kahlow predicts that "When buyers realize their answer is going to be more accurate and more empathetic, they're going to demand to talk to an AI over a human." The traditional role of the sales representative is facing total disruption, and Amanda Kahlow states clearly that in the future "I don't think there will be sellers... I think the best thing we can do for sellers and for the market right now is to be f***ing honest about what is coming for them." Product development for revenue technology must prioritize the end customer over internal efficiency, a philosophy Amanda Kahlow emphasizes by noting that "If I can create a better buying experience, I believe the rest will fall into place... if that's not a better buying experience, I want to be a hard no to it." Connect with the Hosts & Guests: Host: Sam Jacobs - https://www.linkedin.com/in/samfjacobs/  Host: AJ Bruno - https://www.linkedin.com/in/ajbruno3/  Host: Asad Zaman - https://www.linkedin.com/in/azaman1/  Guest: Amanda Kahlow - https://www.linkedin.com/in/amandakahlow/ Topline is more than a Podcast: Subscribe to Topline Newsletter: https://www.joinpavilion.com/topline-newsletter  Tune into Topline on YouTube, the #1 podcast for founders, operators, and investors in B2B tech: https://www.youtube.com/@TOPLINE-Media Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters (Audio Version): 01:00 Introducing Amanda Kahlow and 1mind 02:27 What are Go To Market Superhumans? 06:50 Managing AI Latency and Models 09:53 AI: More Trustworthy Than Human Sellers 15:40 Building the Future of GTM Tech 22:25 The Next Three Years of GTM 35:16 Closing Six Figure Enterprise Deals 40:01 Will Sales Reps Exist in Two Years? 50:00 Collapsing the Sales Assembly Line 54:08 Adapting to the AI Sales Era 58:36 The Autonomous Context Graph Future   

Klik je týždenný komentovaný prehľad technologických správ, o udalostiach, ktoré sa udiali vo svete IT, médií a sociálnych sietí. Moderátori: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ondrej Podstupka⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Martin Hodás Discord diskusný server nájdete tu: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://discord.gg/eqeqBcw2V8⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Linky: OpenAI náhle zarezalo Soru a zrušilo miliardový deal s Disney Google vo výsledkoch vyhľadávania bez súhlasu prepisuje titulky novinových článkov DLSS 5 debakel pokračuje BYD nabíja auto za päť minút Meta už nedostáva pokuty len v Európe, ale aj v domovských USA Musk prehral súd s investormi X, klamal o počte botov Starlink na SK zlacnil a zrušil poplatok za HW Misia Artemis asi čoskoro štartuje Rozhovor The Verge so šéfom AI firmy Superhuman. Spravili sme chybu, máte pripomienku? Napíšte nám na ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠klik@sme.sk⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Kapitoly 00:00 Úvod01:28 AI tragédi týždňa, SORA, NVIDIA, Google24:33 Musk a Meta žaloby a pokuty30:11 Ako budú vyzerať pumpy v budúcnosti36:26 HW drobnosti41:21 ZáverSee omnystudio.com/listener for privacy information.

Hala Hanina is joined in the Palestine Deep Dive studio by Dr Bahzad Ziyad, a Palestinian medical doctor and mental health specialist who survived two years of Israel's genocide on Gaza.This episode of Falasteeniya exposes the romanticisation of Palestinian resilience as yet another form of dehumanisation while reclaiming Palestinian humanity in its full, ordinary complexity.Dr Bahzad has previously lived in the United Kingdom while studying for a masters degree in Child and Adolescent Mental Health at King's College London, before choosing to return home to Gaza to serve his people as a mental health doctor at the Gaza Community Mental Health Program. Hala Hanina is a social and political activist from Gaza. She is currently completing a PhD in politics and sociology, focusing on Palestinian women at the intersection of colonial and patriarchal violence.Support independent, Palestinian-led media from as little as £1 per month: https://www.palestinedeepdive.com/p/support

We're a team of 6 people who built a profitable startup, and we couldn't have done it without AI. In this video, I'm breaking down every single AI tool we use to stay lean, ship fast, and avoid burnout. If you're a founder, solopreneur, or anyone building a business in 2026, this is your complete AI toolkit. I'm sharing the exact tools we use for social media, video editing, admin work, customer support, and development—plus how we implement them to 10X our productivity. ⚡ TOOLS MENTIONED:

Wim Hof aka “The Iceman” joins the boys to discuss how humans can live 200+ years and cure depression & disease, climbing Mount Everest in shorts, being 67-years-old but having an 18-year-old heart, collabing with Drake, hanging from a hot air balloon string with 1 finger, cold and breathing exercises EVERY person should be doing daily, having a 42-year-old son & 1-year-old daughter, the real way athletes can prevent concussions, running for president, his 100% proven way to cure hangovers & more..SUBSCRIBE TO THE PODCAST ► https://www.youtube.com/impaulsiveText LOGAN42 to 4-THE-PEOPLE (484-373-6753) . Enter for a chance to win $2,000 + 2x WrestleMania 42 Tickets. NO PURCHASE NECESSARY. Open to legal residents of the 48 contiguous United States and D.C., who are 18+. Sweepstakes ends 3/29/2026. This is a paid advertisement.Tickets are on sale now at https://www.wweworld.com/wrestlemania-42. Save 10% with promo code IMPAULSIVE10Fanatics Fest Tickets are on sale now at https://www.fanaticsfest.com/ . Grab yours today and we'll see you there!!Who will win the NCAA Mens tournament? https://polymarket.com/event/2026-ncaa-tournament-winnerVisit https://www.wimhofmethod.com/ to learn more about the Wim Hof Method and its benefits.To start practicing the method, download the Wim Hof Method app (iOS or Android).For a free introductory Wim Hof Method miniclass, sign up here https://www.wimhofmethod.com/free-mini-classWatch Previous (Bradley Martyn on SteveWillDoIt Vs NELK BEEF, Fist Fighting Logan Paul, Clavicular Surpassing Tate) ► https://www.youtube.com/watch?v=ZAdZHiLvroM&t=2sADD US ON:INSTAGRAM: https://www.instagram.com/impaulsiveshow/Timestamps:0:00 Welcome Wim Hof

Today, I'm talking with Shishir Mehrotra, the CEO of Superhuman, the company formerly known as Grammarly, which is still its flagship product. Back in August, Grammarly shipped a feature called Expert Review, which allowed you to get writing suggestions from AI-cloned “experts,” and recently, reporters at The Verge and other outlets discovered that those experts included me, among many others.  No one ever asked permission to use our names this way, and a lot of reporters were outraged by this. To Shishir's credit, he did not cancel our interview and he came on and stuck it out. This conversation got tense at times, and it's clear we disagree about how extractive AI feels for people. There's a lot in this one, and I'm excited to hear what you think. Links: Why I'm suing Grammarly | New York Times Grammarly will stop using identities without permission | The Verge Grammarly to keep using writer identities unless they opt out | The Verge Grammarly turned me into an AI editor and I hate it | Platformer Grammarly is using our identities without permission | The Verge Grammarly is changing its name to Superhuman | The Verge Grammarly wants to become an ‘AI productivity platform' | The Verge Viacom v. YouTube, 2007 | Electronic Frontier Foundation Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt. This episode was edited by Xander Adams. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Everyday Genius: Hacks to Boost Your Memory, Focus, Problem-Solving, and Much More by Nelson Dellis Nelsondellis.com https://www.amazon.com/Everyday-Genius-Hacks-Memory-Problem-Solving/dp/1419784811 What if genius isn’t something you’re born with―it’s something you build? Everyday Genius, by six-time USA Memory Champion Nelson Dellis, upgrades your everyday life through practical skills, whether it’s memorizing names at a new job, doing lightning-fast mental math when it counts, honing decisive intuition, and beyond. Written by Remember It! author Nelson Dellis and with a foreword by New York Times bestselling author Barbara Oakley, Everyday Genius teaches you the skills that make genius-level thinking accessible to anyone. Better memory. Sharper focus. Faster learning. Creative problem-solving. No natural talent required, just the right methods. In 2009, after watching his grandmother struggle with Alzheimer’s, Nelson Dellis set out to strengthen his own mind. That mission led to six USA Memory Championships, two Guinness World Records, and a career dedicated to proving that anyone can develop genius-level cognitive abilities. Everyday Genius teaches you to memorize names and faces instantly, speed-read with deep comprehension, calculate mentally with surprising accuracy, and focus intensely when it matters most. You’ll learn strategies for chess and strategic games, techniques for acing exams and public speaking, and methods for creative problem-solving that help you see connections others miss. From mastering a Rubik’s Cube to holding complex ideas in your head, from reading a room to thinking on your feet―this book gives you the mental toolkit for a sharper, more engaged life. At a time when outsourcing our thinking has never been easier, Everyday Genius shows you how to reclaim and strengthen your most valuable asset: your brain. You have far more potential than you realize―an inner genius waiting to be awakened. This book unlocks it. Dellis breaks down complex mnemonic systems into digestible, actionable strategies. By following his lead, you will learn: Memory Mastery Speed Reading Focus and Concentration Learning Mastery Mental Calculation Problem-Solving and Creativity Strategic Thinking Social Skills Mastery Beyond Genius About the author Nelson Dellis is a 4x USA Memory Champion and one of the leading memory experts in the world, traveling around the world as a competitive Memory Athlete, Memory Consultant, Published Author and highly sought-after Keynote Speaker. As a Memory Champion, Mountaineer, and Alzheimer’s Disease Activist, he preaches a lifestyle that combines fitness, both mental and physical, with proper diet and social involvement. Born with an average memory, Nelson was inspired by the passing of his grandmother from Alzheimer’s disease in 2009 to start training his memory so that he could keep his mind strong and healthy throughout his lifespan. In a short period of time, he transformed into one of the leading competitive memorizers in the world, claiming four U.S. titles along the way, the elite Grandmaster of Memory title, as well as a number of U.S. memory records for: – Memorizing the most names in 15 minutes – 217 names – Memorizing the most words in 15 minutes – 256 words – Memorizing the most digits in 30 minutes – 907 digits – Memorizing the most decks of playing cards in 30 minutes – 9.02 decks – (former record) Memorizing the most digits in 5 minutes – 339 digits – (former record) Memorizing a deck of cards in the fastest time – 40.65 seconds Nelson is the Founder & CEO of Climb For Memory, a non-profit charity that aims to raise awareness and funds for Alzheimer’s disease research through mountain climbs all around the world. Nelson has climbed numerous peaks around the world for this cause, including three times on Mt. Everest. Nelson has been featured on FOX’s Superhumans, The TODAY Show, Fox and Friends, The Katie Couric Show, CNN.com, ABC Nightline, The Dr. Oz Show, The Science Channel, Nat Geo, SuperBrain China, among many other media outlets.

This Week In Startups is made possible by:Northwest Registered Agent - https://www.northwestregisteredagent.com/twistCircle - https://circle.so/twistNetsuite - https://www.netsuite.com/twistToday's show:Zipline founder Keller Cliffton started his company with a simple premise: build automated logistics that serve everyone equally. The only problem? It was literally illegal in the US.In this live recording from LaunchFest in San Francisco, Keller shares how Zipline went from a 20-person team working on a cow farm in Rwanda to operating the largest commercial autonomous system on Earth. They now complete 130 million autonomous miles with zero accidents, while reducing maternal mortality by 51% in the regions they serve.PLUS we've got Rahul Vohra from Superhuman taking us through his entire founder journey, and discussing with Jason why “difficult” founders are often the smartest investments.Timestamps:0:00 Intro1:16 Keller Cliffton starts off the show3:05 Starting Zipline in Africa8:40 The magic of sky maps13:55 Building the drone was just the beginning15:11 Making a huge difference in maternal mortality23:48 The threats of Little Evil Jimmy and dogs29:37 The shift from Rwanda to Dallas31:14 Netsuite - Get the free business guide Demystifying AI at https://www.netsuite.com/twist32:28 The moral clarity of the mission41:17 The challenge of staying focused46:43 Rahul Vohra of Superhuman joins Jason49:40 Building Rapportive in Cambridge51:48 Scaling to millions of users via APIs1:11:46 How getting acquired made Rahul fearless1:12:31 The boldness of taking on Gmail1:22:12 Making everyone pay for the product1:31:24 Inside the Grammarly-Superhuman dealSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisCheck out all our partner offers: https://partners.launch.co/Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

In August 2021, the world watched in disbelief as Afghanistan collapsed, leaving two decades of sacrifice, hope, and war in question. America's longest war, forged in the aftermath of 9/11 and costing thousands of lives and billions of dollars, ended in chaos, confusion, and the swift return of the Taliban. But what truly happened in those final, frantic days? Who held the line until the line was irrevocably gone?In this exclusive interview, host Fran Racioppi sat down with General Haibatullah Alizai, the final Chief of the Afghan National Army, now living in exile. General Alizai offers a raw, firsthand account of the challenges, the political decisions, and the human cost that led to the nation's swift downfall. From the initial hope sparked by the post-9/11 intervention to the crushing weight of the Taliban's propaganda machine, he confronts the harsh realities faced by Afghan forces and the devastating decisions that altered the course of history.Discover the candid perspective of a warrior who fought for a country that no longer exists. General Alizai speaks on loyalty, the pervasive impact of corruption, the strategic failures that enabled the Taliban's resurgence, and his powerful message to the American service members who served alongside him.War provides Warriors perspective. Is it possible to reclaim what was lost? And was the 20-year commitment truly worth the cost? Dive into the complexity of war, the human reality behind America's longest conflict, and the future of a nation still searching for stability in the shadow of the Taliban. This is the untold story of the Afghan Army's last stand.HIGHLIGHTS0:00 Introduction1:51 Welcome to the Jedburgh Podcast5:11 Afghanistan, 200119:23 America's Goal In Afghanistan28:51 Afghan Sentiment30:00 Taliban Propaganda36:39 Taliban Today43:30 US Soldiers in Afghanistan49:29 Can Afghanistan be reclaimed?52:51 Leaving Family59:20 Future of AfghanistanQuotes:“You have to have a steel-made ass to be in the Army.”“Kunduz collapsed in September 2015 because coordination was poor.” “We are not going to sit. We are going to solve the problem.”“In the last five days of collapse, I became the Chief of the entire Army.”“I believe the Americans came to Afghanistan to punish their enemies who coordinated the attack in New York.”“Who else has fought more than Afghans for freedom.”“They started with chopping heads.”“The poppies became popular during the first Taliban term.”“They all became strength points to the Taliban and weak points to us.” “When we really understood what was going on, it was a bit too late.” “The only thing the Taliban is still doing is brutality.”“Before the US came to Afghanistan, there was a civil war.”“Now we have thousands of warlords in Afghanistan.”“We lost thousands of people and all those lives were dedicated to support the humanity and democracy the right way."“Have we left something unfinished?”“We should find a way to finish the unfinished business.”“The Taliban has destroyed the Afghan history and honor.”“The Taliban are 10 times more vulnerable than 2001.”“Next is change. It has to happen.”“It will be a question that will bring hesitation.”“I believe we are just a whistle away from bringing the change in Afghanistan.”“What country in the world can do everything on their own?”The Jedburgh Podcast is brought to you by Onebrief; enabling military leaders to make innovative, informed and deliberate decisions faster than ever before. Superhuman command wins wars.Follow the Jedburgh Podcast and the Green Beret Foundation on social media. Listen on your favorite podcast platform, read on our website, and watch the full video version on YouTube as we show why America must continue to lead from the front, no matter the challenge.

Hunter and Taylor sit down in person with Alex Kikel — biohacker, performance coach, and one of the most forward-thinking minds in the peptide and longevity space — for one of the most information-dense conversations the podcast has ever had.In this episode, they go deep on the science of coherent vs. non-coherent EMF and why it matters more than most people realize, structured water and how your environment is either working for or against your biology, and the cutting-edge peptide molecules Alex believes will define the next era of human optimization — including KLP-1, VD-11, and FoxO3.They also cover GLP-1s and where the conversation is really headed, fertility and pregnancy optimization for couples on hormone therapy, postpartum recovery protocols, non-androgenic muscle building strategies, PBO walks and active manifestation, and Alex's vision for what a true "super molecule" could mean for human evolution.Whether you're deep in the biohacking world or just getting started, this episode will challenge how you think about your health, your environment, and what's actually possible.Watch on Youtube: https://youtu.be/tYscWLLPkDE

Dan Moren of SixColors joins Mikah Sargent again on Tech News Weekly! Grammarly is facing a class action lawsuit over its AI "Expert Review" feature. Live Nation's settlement with the DOJ does very little. A recap of Mobile World Congress in Barcelona, Spain. And China is obsessed with OpenClaw AI. Dan talks about a class-action lawsuit brought against Grammarly and its company, Superhuman, over its AI "Expert Review" feature that offered editing suggestions as if they came from various authors and academics, without their consent. Mikah, and many others, are perplexed at the DOJ's settlement with Live Nation Entertainment and what little Live Nation had to concede as part of the settlement. Abrar Al-Heeti of CNET stops by to share her experience at MWC (Mobile World Congress) in Barcelona and what she and her CNET colleagues saw there. And Mikah shares about China's obsession with the OpenClaw AI craze and how users are utilizing the AI agent. Hosts: Mikah Sargent and Dan Moren Guest: Abrar Al-Heeti Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT zscaler.com/security hipebl.ai

Dan Moren of SixColors joins Mikah Sargent again on Tech News Weekly! Grammarly is facing a class action lawsuit over its AI "Expert Review" feature. Live Nation's settlement with the DOJ does very little. A recap of Mobile World Congress in Barcelona, Spain. And China is obsessed with OpenClaw AI. Dan talks about a class-action lawsuit brought against Grammarly and its company, Superhuman, over its AI "Expert Review" feature that offered editing suggestions as if they came from various authors and academics, without their consent. Mikah, and many others, are perplexed at the DOJ's settlement with Live Nation Entertainment and what little Live Nation had to concede as part of the settlement. Abrar Al-Heeti of CNET stops by to share her experience at MWC (Mobile World Congress) in Barcelona and what she and her CNET colleagues saw there. And Mikah shares about China's obsession with the OpenClaw AI craze and how users are utilizing the AI agent. Hosts: Mikah Sargent and Dan Moren Guest: Abrar Al-Heeti Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT zscaler.com/security hipebl.ai

Dan Moren of SixColors joins Mikah Sargent again on Tech News Weekly! Grammarly is facing a class action lawsuit over its AI "Expert Review" feature. Live Nation's settlement with the DOJ does very little. A recap of Mobile World Congress in Barcelona, Spain. And China is obsessed with OpenClaw AI. Dan talks about a class-action lawsuit brought against Grammarly and its company, Superhuman, over its AI "Expert Review" feature that offered editing suggestions as if they came from various authors and academics, without their consent. Mikah, and many others, are perplexed at the DOJ's settlement with Live Nation Entertainment and what little Live Nation had to concede as part of the settlement. Abrar Al-Heeti of CNET stops by to share her experience at MWC (Mobile World Congress) in Barcelona and what she and her CNET colleagues saw there. And Mikah shares about China's obsession with the OpenClaw AI craze and how users are utilizing the AI agent. Hosts: Mikah Sargent and Dan Moren Guest: Abrar Al-Heeti Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT zscaler.com/security hipebl.ai

Dan Moren of SixColors joins Mikah Sargent again on Tech News Weekly! Grammarly is facing a class action lawsuit over its AI "Expert Review" feature. Live Nation's settlement with the DOJ does very little. A recap of Mobile World Congress in Barcelona, Spain. And China is obsessed with OpenClaw AI. Dan talks about a class-action lawsuit brought against Grammarly and its company, Superhuman, over its AI "Expert Review" feature that offered editing suggestions as if they came from various authors and academics, without their consent. Mikah, and many others, are perplexed at the DOJ's settlement with Live Nation Entertainment and what little Live Nation had to concede as part of the settlement. Abrar Al-Heeti of CNET stops by to share her experience at MWC (Mobile World Congress) in Barcelona and what she and her CNET colleagues saw there. And Mikah shares about China's obsession with the OpenClaw AI craze and how users are utilizing the AI agent. Hosts: Mikah Sargent and Dan Moren Guest: Abrar Al-Heeti Download or subscribe to Tech News Weekly at https://twit.tv/shows/tech-news-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: bitwarden.com/twit joindeleteme.com/twit promo code TWIT zscaler.com/security hipebl.ai

Mar 9, 2026 – What if the secret to reversing the aging process wasn't found in a pill, but in the fundamental elements of nature? Jason Tebeau reveals the Superhuman Protocol, a groundbreaking three-step system designed to "recharge"...

In today's minisode, AI pioneer and enterprise sales leader Amanda Kahlow shares why intent data as we know it is dying – and what replaces it. Amanda is the founder and CEO of 1mind. In this segment, she discusses how SI  “superhumans” can operate inside live deals with access to every document and data point, and why the future of go-to-market may move toward agent-to-agent negotiation… with humans stepping in only for the final mile. If you're a CRO rethinking your funnel, a sales leader questioning the future of the SDR role, or an operator trying to understand how AI fits into active pipeline management, this episode is for you. Amanda Kahlow is the Founder and CEO of 1mind and the Founder of Sixth Sense. She is a multi time enterprise founder building AI systems designed to transform the full go-to-market lifecycle. Connect with Amanda: LinkedIn 1mind Get the Force Management guide to adapting your go-to-market execution for the AI age: The Predictable Revenue Framework: Guide for Leaders Hosted by five-time CRO John McMahon and Force Management Co-Founder John Kaplan, the Revenue Builders podcast goes behind the scenes with the sales leaders who have been there, done that, and seen the results. This show is brought to you by Force Management. We help companies improve sales performance, executing their growth strategy at the point of sale. Connect with Us: LinkedInYouTubeForce Management

AI is getting dangerously good at smart contract security. Faster than crypto is ready for. Alpin Yukseloglu joins Bankless to break down EVMBench (built with OpenAI), a benchmark testing whether AI agents can detect, patch, and exploit real fund-draining bugs and why the jump from ~12–13% exploit-finding to 70%+ could rewrite today's security assumptions. We unpack what that “70%” really means, why crypto's verifiability is an ideal training ground, why AI labs haven't prioritized crypto data yet, and what a 24/7 blackhat vs whitehat AI arms race means for DeFi. ---

Every startup hits the same ceiling: your founder customers love you, but they won't get you to $200M. So how do you move upmarket to enterprise without losing the community that built you? Harmony Anderson, VP of Growth & Marketing at Superhuman, gets into the real mechanics of it: The 70/30 resource split between enterprise and community Why she's hiring a "startup evangelist" to hold down their founder base Why they didn't need a rebrand to start winning enterprise deals What she learned studying how Canva pulled off the same shift Plus, Harmony's vision for where AI-native productivity is actually headed and why the line between your personal and professional tools is about to disappear. If you enjoyed this clip, be sure to check out the full episode on Marketing Trends: The Secret To Scaling From $20 Million to $200 Million ARR (Extremely Fast)  ----Mission.org is a media studio producing content alongside world-class clients. Learn more at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Meet Mimi Bouchard, founder of Superhuman, the motivational audio app that makes transforming your life effortless and inevitable. In this powerful episode, Krista + Mimi discuss the potent tools they use to manifest, including visualization and affirmations. Morning Microdose is a podcast curated by Krista Williams and Lindsey Simcik, the hosts and founders of Almost 30, a global community, brand, and top rated podcast. With curated clips from the Almost 30 podcast, Morning Mircodose will set the tone for your day, so you can feel inspired through thought provoking conversations…all in digestible episodes that are less than 10 minutes. Wake up with Krista and Lindsey, both literally and spiritually, Monday-Friday. If you enjoyed this conversation, listen to the full episode on Spotify here and on Apple here.