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1:06:02ENYann LeCun on Open AI Models, Safety and the Future of ResearchGuest Yann Lecun · Host Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.
1:42:48ENThe Skype Co-Founder Who Wants a Six-Month Pause on Frontier AIHost Nathan LabenzJaan Tallinn argues that each 10× jump in training compute carries a 1 to 50 percent chance of ending everything, and that the labs still will not say when they will stop.
1:09:54ENA $100 Doctor Visit and a $1 AI: GPT-4 Was Already Unbundling WorkHost Nathan LabenzBefore GPT-4 launched, Nathan Labenz spent two months making the model play a dozen paid professions, then argued with Erik Torenberg about what that does to jobs, regulation, and white-collar status.
1:33:49ENSafe Only Because It's Weak: A GPT-4 Red-Teamer and Two Founders Debate the PauseHost Nathan LabenzNathan Labenz, who spent six months trying to make GPT-4 misbehave, wants labs to stop training anything bigger; Chroma's Anton Troynikov and Lindy's Flo Crivello argue a six-month freeze buys little and may select for the least careful labs.
11:28ENCan AI Development Be Paused? The 2023 Open Letter and Its Trade-OffsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines the call to pause training systems more powerful than GPT-4, the concerns behind it and the difficulties of coordination.
3:08ENDavid Guetta’s AI-Generated Eminem Voice and the Questions It RaisesMatthew Berman, David Guetta · Forward FutureMatthew Berman discusses a synthetic vocal played during a DJ set and considers consent, creative use and possible legal disputes.
1:44:47ENErik Brynjolfsson on the Exponential Mismatch Remaking Work and PoliticsGuest Erik Brynjolfsson · Host Lex FridmanThe Stanford economist tells Lex Fridman why COVID, AI, and social networks all punish linear intuition — and why shared prosperity is the only way the pie-growing story holds.
1:48:55ENThree Fairness Rules That Cannot All Be TrueGuest Michael Kearns · Host Lex FridmanMichael Kearns tells Lex Fridman why algorithmic fairness is messier than privacy, and why a Pareto curve belongs in front of the people who actually have to choose.
1:00:38ENThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle SafetyHost Lex FridmanA Stanford engineer and former DOT innovation chief explains how autonomous racing, voluntary safety guidance, and data sharing could shape safer self-driving cars.
1:23:56ENA Three-Month Window: The AI 2027 Authors on Superhuman Coders, Faked Alignment and Who Ends Up in ControlHost Jacob EffronDaniel Kokotajlo and Thomas Larsen walk through their AI 2027 scenario, where they disagree on timelines and alignment, and what they think governments and the public should do.
53:39ENA Libertarian's Case for Regulating AI: Kill Switches, Chip Choke Points and a New Form of LifeHost Nathan LabenzLindy founder Flo Crivello explains why a self-described accelerationist makes an exception for superintelligence, and what he thinks of Biden's executive order.
47:13ENReid Hoffman's Case Against Doomerism: AI as the Steam Engine of the MindHost Sarah Guo, Elad GilThe LinkedIn and PayPal co-founder explains why he sees AI as a human amplifier, what white-collar workers should do now, how Inflection's Pi was conceived, and why you can't regulate before you innovate.
1:12:15ENThe Open-Model Vibe Check: China, Containment, and the Data MoatHost Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.
2:18:07ENGambling on Trump for the AI Era: Nathan Labenz and Samuel Hammond Argue the StakesHost Nathan LabenzA long, good-natured debate over whether Trump's high-variance, ideas-driven coalition or a stable incrementalist Democratic establishment is the better bet for governing AI, China policy and a possible intelligence explosion.









