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1:48:57ENAI Safety's Real Shortage Is Founders, Not Ideas진행자 Nathan LabenzHalcyon's Mike McCormick on launching about 30 AI safety, cyber, and biosecurity organizations in three years — and why experienced leaders, not more Google Docs, are the bottleneck.
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.
1:13:48ENCarriers 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.
1:55:12EN28,000 Documents, a 3B Model, 22 People: The Technical Ledger of Catholic AI진행자 Nathan LabenzLongbeard CEO Matthew Harvey Sanders tells The Cognitive Revolution how a mission-driven team is aligning models to the Catholic magisterium — and why fine-tuning was not enough.
1:02:05EN$100 Million Researchers and a $200 Billion xAI: An AI Roundtable Does the Math진행자 Jacob EffronDatology’s Ari Morcos and Radical Ventures’ Rob Toews argue over whether models are plateauing, whether RL-environment startups will last, and why Google is the lab they would pick.
1:51:39ENA native ad engine for AI—and the questions it cannot dodge진행자 Nathan LabenzRyan Hudson, who sold Honey to PayPal for $4 billion, joins Nathan Labenz to explain ZeroClick’s bet on paid inference-time ads, and the societal incentives he has not yet had to confront.
57:52ENThey Aimed for 1%. The Lab Hit 20%. Chai Discovery Moved Antibody Design Onto the Computer.진행자 Jacob EffronJoshua Meier on three waves of AI drug discovery, why Chai-2 behaves like Photoshop for molecules, and why a 1% hit rate was supposed to be enough to change the industry.
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.
1:24:27EN500 Trillion Tokens a Month: How Google Grew 50x in a Year진행자 Nathan LabenzLogan Kilpatrick returns to Cognitive Revolution to unpack Google's mid-2023 merger, why he expects frontier labs to diverge, and why startups still hold the speed advantage.
1:00:48ENThe Phrase That Alarms a16z’s AI Policy Chief: “It Only Covers a Handful of Companies”진행자 Nathan LabenzMatt Perault argues that AI rules should target harmful use, not the science of building models, and that “modest” thresholds can lock in an oligopoly.
44:21ENMercor's CEO: Knowledge Work's Next Job Is Writing Evals진행자 Jacob EffronBrendan Foody tells Redpoint how Mercor turned AI hiring and expert data into a $100 million round — and why he thinks a huge slice of white-collar work will become creating tests for models.
1:54:08ENWhy Anthropic's first check went to a company building microscopes for neural nets진행자 Nathan LabenzGoodfire's Dan Balsam and Tom McGrath argue that mechanistic interpretability now has a proto-paradigm, two stubborn gaps, and three products worth shipping today.
43:51ENThe $177 Billion GPU Bet Only Works If AI Becomes a $1.5 Trillion Market진행자 Jacob EffronFour Redpoint partners walk their limited partners through where AI value will accrue—and why revenue is now the easiest metric to misread.
1:27:33ENA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a Day진행자 Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.
1:06:15ENJailbreaks Got Harder. Scale Made One Attack Worse.진행자 Nathan LabenzHaize Labs spent a month automatically attacking OpenAI's o1. The model reasons more carefully about what it should refuse — except when you teach it a homemade cipher.
1:52:00EN4,096 Numbers Have to Carry Every Concept. Goodfire Wants the Knobs진행자 Nathan LabenzDan Balsam and Tom McGrath explain how sparse autoencoders unpack a language model's residual stream — and why a public-benefit startup is trying to make that a product.
1:03:22ENA 40-person team at $35 million ARR: HeyGen made AI avatars a business, not a demo진행자 Nathan LabenzJoshua Xu and Benchmark’s Victor Lazarte tell Nathan Labenz how a camera-replacement product grew past 40,000 business customers — and why half the faces on this episode are fake.
1:32:45ENHe doubled a company with AI — then asked the labs to pause hyperscaling진행자 Nathan LabenzOn the Nick Halaris Show, Cognitive Revolution host Nathan Labenz argues for adopting today's models fast and slowing the race to systems more powerful than we are.
52:45ENA $150 million model, $5 million six months later: Benchmark’s AI investment math진행자 Nathan LabenzEric Vishria and Quilter’s Sergiy Nesterenko explain why PCB layout is not a Copilot problem, why human board data would be the wrong training set, and which AI companies look like sugar highs.
56:56ENA Week of PCB Layout in an Hour: Quilter Trains Agents, Not Imitators진행자 Nathan LabenzSpaceX alum Sergiy Nesterenko tells Will Summerlin how Quilter uses reinforcement learning to compile schematics into manufacturable boards, and why cloning human layouts would cap the system at human skill.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%진행자 Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.
1:32:19ENHis 2018 Prompting Paper Was Rejected. His Search API Now Beats Google진행자 Nathan LabenzRichard Socher traces You.com from a rejected unified NLP model to an LLM-native web index, three assistant modes, and a very low P(doom).
1:01:53ENCompanion Apps Open Twice as Often as TikTok. a16z Only Funds Weird but Working진행자 Nathan Labenza16z consumer partners Anish Acharya and Justine Moore walk Nathan Labenz through their Abundance Agenda for AI-native consumer apps.
1:21:28ENThe Prompt Is a Bug: Suhail Doshi’s Bet on Control Over Pixels진행자 Nathan LabenzThe Mixpanel founder tells Nathan Labenz how a cloud browser, a canceled tweet, and a Thursday weight drop shaped Playground AI’s bet on images.
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