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2:16:29ENFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI Safety진행자 Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
34:30ENNetic's Agents Answer the Phone When the Heat Breaks진행자 Sarah Guo, Elad GilFounder Melisa Tokmak tells Elad Gil how a two-year-old platform became the AI operations layer for HVAC, roofing, pet care, and other essential services.
1:04:14ENThe Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your House진행자 Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.
1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can Win진행자 Nathan LabenzAdam Gleave walks through FAR.AI’s first head-to-head AI security leaderboard, and explains why a decade of offense-dominant thinking is starting to crack.
49:12ENThe People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
3:46:18ENIf You Take Slavery Out of the Picture, There Is No Civil War게스트 Gary Gallagher · 진행자 Lex FridmanIn 1860, enslaved people were worth more than every railroad and factory in the United States combined.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His Inbox진행자 Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
49:20ENHalf of Ask DoorDash Orders Hit a New Restaurant. In Ten Years There Will Be More Dashers, Not Fewer.진행자 Sarah Guo, Elad GilCo-founders Andy Fang and Stanley Tang tell Sarah Guo how a conversational ordering interface moved DoorDash's hardest metric, why they built a 300-pound delivery robot in-house, and why autonomy means more human riders, not less.
51:31ENThey Refunded Nearly $2 Million. Then Factory’s CEO Explained the Dark FactoryMatan Grinberg on being two years early, why a model-agnostic harness beats lab co-design, and why 90 percent of coding tokens will soon run with the lights off.
1:13:48ENCarriers Spend $200 Billion a Year. The Money Went Up the Stack진행자 Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.
48:55ENAnthropic's Platform Grew Three Layers in a Year — and Tokens Now Have JobsKatelyn Lesse and Angela Jiang tell Sequoia's Training Data how Anthropic went from a stateless Messages API to knowledge, execution, and coordination — without trying to own the servers.
2:23:38ENDavidad Cut His p(doom) From the Seventies to Under 5% — and Named a Bodhisattva as the Alignment Target진행자 Nathan LabenzThe former ARIA Safeguarded AI director tells Cognitive Revolution why boxing superintelligence is too late, why he thinks models are climbing a U-shaped wisdom curve, and why the remaining risk is a race you cannot monitor.
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token One진행자 Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
50:57ENA Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuber진행자 Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.
41:05ENThere is no moat: Booking’s CEO on a $1 stock, agentic travel, and why AI still doesn’t move the numbers진행자 Sarah Guo, Elad GilGlenn Fogel cashed his 1999 bonus, joined Priceline in February 2000, and watched the Nasdaq peak a week later — then spent 25 years turning a near-delisting into a thousand-fold ride he now wants to spend on AI travel agents.
55:19ENThe drone is 15% of Zipline: 140 million miles, zero incidentsKeller Rinaudo Cliffton and Eric Watson explain why the aircraft is the small part of an automated logistics system now cheaper than a car.
1:47:38EN19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip진행자 Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
1:01:27ENTwo Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times Cheaper진행자 Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.
1:29:02ENFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Explore진행자 Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
3:51:47ENForty-Six Percent of Emperors Were Overthrown. The Empire Lasted Anyway게스트 Anthony Kaldellis · 진행자 Lex FridmanHistorian Anthony Kaldellis walks Lex Fridman through 2,200 years of Roman history and argues that what we call Byzantium was Rome itself.
1:10:15ENThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.
1:57:46EN30% Consciousness, 47% Bee, 80% Turnover: Putting Numbers on What AI Is Becoming진행자 Nathan LabenzA Cognitive Revolution weekly cut that starts inside the model with Cameron Berg, then zooms out through gradual disempowerment, Europe’s bind, and the companies rebuilding around agents.
36:19ENThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score Models진행자 Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
44:52ENAn 80GB Wikipedia Cache Versus a 100GB Model That Holds the InternetEngram’s founders argue that stuffing a company into the context window is the expensive kind of memory—and that baking it into the weights can cut token use by two orders of magnitude.
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