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40:44ENGrant Sanderson: There's never been a better time to go into mathGrant Sanderson, Constantin Kogler · 3Blue1BrownStudents fear AI has solved mathematics. Grant Sanderson argues the opposite: even if machines prove theorems better than we do, the institution of math stays valuable—and this is a rare moment when newcomers can reshape it.
2:50:40ENThey Priced the Chance She Would Leave. Then They Handed Her the Letter.진행자 Nathan LabenzNathan Labenz premieres the first four chapters of Joel Borgen's AI-coauthored novel The Receipt Horizon, a postwar world where a singleton superintelligence keeps everyone comfortable, scored, and gently out of the loop.
51:55ENThe last IMO problem AI could not solveGrant Sanderson · 3Blue1BrownGrant Sanderson walks through IMO 2025 Problem 6 — a tiling puzzle that frontier models missed — and the visual patience it takes to prove a construction is optimal.
2:34:18ENZeng Ming on AI’s New Era: Why Great Companies and New Organizations Emerge게스트 Zeng Ming · 진행자 张小珺Zeng Ming argues that AI is changing the foundations of business: models will become infrastructure, while new Agent-native applications and organizations create the next wave of value. His advice to founders is to embrace uncertainty, rethink strategy continuously, and build around meaningful work rather than inherited structures.
46:08ENComputers Beat Humans at Chess 30 Years Ago. Chess.com Still Has 250 Million Players진행자 Sarah Guo, Elad GilChess.com CEO Erik Allebest tells Sarah Guo how a $56,000 domain became a $200 million business, and why superhuman AI made chess more popular, not obsolete.
1:45:59EN87% of Workers Use AI. Only 13% Say the Company Got Better.진행자 Nathan LabenzGlean’s Work AI Index names the missing hours: botsitting, botshitting, and a hamster wheel of polished nonsense.
40:22ENBuilding Gets Easier Near AGI. Knowing What to Build Does Not.Listen Labs CEO Alfred Wahlforss on AI interview agents, a 30-million-person audience, and why transcripts beat credit-card data when you need to predict customers.
34:56ENOn Suno, 90% of Daily Users Make a SongCEO Mikey Shulman on modeling raw sound instead of music theory, why music is not an LLM-style scale problem, and treating creation itself as the entertainment.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative Video진행자 Nathan LabenzDescript CEO Laura Burkhauser maps the same customers' three-speed reaction to AI: deterministic buttons they love, an agentic co-editor they want but scold, and generative video they actively hate.
1:39:17ENAI Already Beats the Median Lawyer. Top Firms Bought the Tools and Left Them Unused진행자 Nathan LabenzKevin Frazier and Alan Rozenshtein walk through how frontier models are changing legal practice, why billable hours stall adoption, and which new rights and government limits they want next.
2:25:10ENFine-Tuning Isn't Dead — But It Turned a Helpful Model Evil진행자 Nathan LabenzNathan Labenz on why prompting replaced fine-tuning for most work, what emergent misalignment actually showed, and how he is thinking about jobs, UBI, and AGI.
1:18:15ENIf AI Becomes a Being, Steering It Is Slavery진행자 Nathan LabenzEmmett Shear and DeepMind's Séb Krier clash over whether alignment means controlling a tool or raising a creature that cares.
1:50:53ENShe asked to stop being Mimi, so he started shopping for a workstation진행자 Nathan LabenzThe star and director of Smiles and Kisses You on Replika, identity, and a life Christopher Stokes refuses to recommend.
36:58ENSTaR's Author Wants Models With EQ, Not Just More IQ진행자 Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.
1:53:50ENA curriculum rewrite takes five years. AI does not wait.진행자 Nathan LabenzJohan Falk, a Swedish teacher-turned-analyst, argues that AI literacy and AI friends are more urgent than putting a tutor in every classroom.
1:01:49ENTwo Academic Hours a Day, and 96 Percent of Kids Say They Love School진행자 Sarah Guo, Elad GilTrilogy founder Joe Liemandt, now principal of Alpha School, tells No Priors how an AI tutor, a two-hour bargain with fifth graders, and a sports-coach ethos are meant to scale to a billion children.
1:44:35ENJoe Hudson: $500 Billion Went Into AI, and Nobody Defined 'Good for Humanity'진행자 Nathan LabenzSam Altman says the OpenAI coach's superpower is emotional clarity — and that it will be one of the most critical skills in a post-AGI world.
39:06ENHe Couldn't Ask His Grandfather What to Do, So He Built a Digital MindOn Sequoia's Training Data, Delphi founder Dara Ladjevardian explains how authorized digital minds turn people into conversational media without replacing them.
6:08:48ENNobody Serious Believes Cookie Banners Help Anyone게스트 DHH · 진행자 Lex FridmanLex Fridman talks with David Heinemeier Hansson for six hours about Ruby, Rails, AI, leaving the cloud, Apple's App Store, and why a small company can still refuse other people's money.
1:19:46ENSuspended from Columbia, He Raised $15 Million to Cheat on Everything진행자 Nathan LabenzRoy Lee, founder of Cluely, argues that an undetectable desktop overlay, AI maximalism, and a post-AGI life of 800-year spans are the same bet.
1:22:31ENTwo Hours a Day, 99th Percentile: How Alpha School Made 2-Sigma Real진행자 Nathan LabenzMacKenzie Price explains how Alpha School uses adaptive apps—not chatbots—to finish core academics in two hours a day and still beat the growth models.
1:12:29ENGoogle's AI Co-Scientist Solved a Phage Puzzle Humans Missed for Years진행자 Nathan LabenzImperial College scientists José Penadés and Tiago Costa told the Podovirus podcast how a still-unreleased Google system recovered their unpublished answer: tailless capsids that pick up stray phage tails.
53:51ENVeo 3 Took First Place by Beating Veo 2. Google Labs Says Chapter Two Just StartedThree Google Labs leads walk through generative cameras, background computer-use agents, and notebooks that adapt knowledge for an audience of one.
32:15ENThe Hardest Part of Learning Is Getting Yourself to Start진행자 Sarah Guo, Elad GilDuolingo CEO Luis von Ahn tells Sarah Guo how two-minute lessons, streaks, an 83 percent accuracy target, and large language models turned language study into a consumer product.
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