필터 결과
102개정렬
1:09:54ENA $100 Doctor Visit and a $1 AI: GPT-4 Was Already Unbundling Work진행자 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 Pause진행자 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 Politics게스트 Erik Brynjolfsson · 진행자 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 True게스트 Michael Kearns · 진행자 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 Safety진행자 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 Control진행자 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 Life진행자 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 Mind진행자 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 Moat진행자 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 Stakes진행자 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.









