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1:06:04ENDan Gill on Carvana’s Unit Economics, Product Decisions and TurnaroundGuest Dan Gill · Host Harry StebbingsThe Carvana product leader discusses financing, logistics, prioritization and leading through a dramatic market-cap decline.
27:42ENMatthew Berman on Capital, Human Ambition, and a Possible Post-AGI EconomyMatthew Berman · Forward FutureA speculative essay asks whether advanced AI could make wealth more powerful while reducing the leverage people gain from work. Berman explores its implications for mobility, institutions, and meaning.
13:33ENSalesforce’s Agentforce 2.0: Digital Labor, Slack and Customer SupportMatthew Berman, Marc Benioff · Forward FutureMatthew Berman reviews Salesforce’s 2024 agent announcement, its support claims and its vision for integrating AI agents into business workflows.
2:04:45ENo3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-ToeHost Nathan LabenzNathan Labenz walks through OpenAI's o3 scores, deliberative alignment, and why 2024's biggest surprise was beating PhDs while failing to book a calendar invite.
1:15:28ENMike Maples on Seed Investing, Founder Fit and When to SellGuest Mike Maples · Host Harry StebbingsThe Floodgate investor explains his approach to fund economics, exceptional founders, follow-ons and partial exits.
15:34ENSam Altman on AGI and Superintelligence: A 2025 DiscussionMatthew Berman, Ray Kurzweil, Lex Fridman · Forward FutureMatthew Berman examines Altman’s statements about AGI, the singularity and possible AI-driven scientific progress.
3:00ENWhy Sugar Water Makes Diagonal Bands of ColorPolarization, scattering and the curved tube combine to produce a surprising barber-pole pattern.
3:06:39ENZelenskyy Refused to Speak Russian. Then He Explained Why a Pause Is Not PeaceGuest Volodymyr Zelenskyy · Host Lex FridmanUkraine's president tells Lex Fridman why language, NATO, and leverage all come back to a ceasefire that already failed.
3:53:49ENWith One-Twelfth the Data, an Open-Source Vision Model Beat GPT-4oHost Nathan LabenzWill Hardman of Veratai walks Nathan Labenz through two years of vision-language models, from ViT and CLIP to InternVL, BLINK, and Transfusion.
30:29ENHow Researchers Think o1-Style Reasoning Models WorkMatthew Berman · Forward FutureMatthew Berman explains a research survey of policy initialization, rewards, search and reinforcement learning, and the open questions behind reasoning models.
1:01:30ENAutoGen and AG2: Chi Wang and Qingyun Wu on Building Multi-Agent SystemsMatthew Berman, Chi Wang, Qingyun Wu · Forward FutureThe AutoGen creators trace their open-source journey and explain how they approach agent workflows, human oversight and the move to AG2.
1:27:13ZH → English李想: Cars Will Evolve from Transportation into Spatial RobotsGuest 李想 · Host 张小珺理想汽车 CEO 李想 explains why the company is moving from carmaking toward AI: foundation models are an operating system for the AI era, and cars are a way into the physical world. For him, the technology must deliver better experiences, capability and lasting value.
1:57:00ENLess Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI FirstHost Nathan LabenzDoom Debates host Liron Shapira presses OpenAI technical staffer roon on extinction odds, alignment-by-default, and a plan that even he admits is balancing on razor wire.
19:06ENBuilding Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
13:39ENDemis Hassabis on Digital Biology, AlphaFold and the Limits of Classical ComputingMatthew Berman, Demis Hassabis · Forward FutureMatthew Berman reviews Hassabis’s Nobel lecture on protein structure, AI-driven discovery and a speculative question about what classical learning algorithms can model.
27:07ENAfter adding $100 billion a month, Jensen Huang says NVIDIA is selling the data centerHost Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.
2:11:15ENA 50% Chance of Extinction — and a $50 GPT-4 for EveryoneHost Nathan LabenzEmad Mostaque tells Nathan Labenz why he puts p(doom) at even odds, why a five-watt model changes the energy debate, and how the Intelligent Internet would fund universal basic AI with a Bitcoin-like token.
21:02ENReactions to OpenAI’s 2024 o3 Preview: Benchmarks, Cost and LimitsMatthew Berman · Forward FutureMatthew Berman surveys the responses to the o3 preview, from mathematical benchmarks to debates about AGI, compute and reliability.
3:26:39ENThe Pessimism Line: Why Earth Is Almost Certainly Not the First CivilizationGuest Adam Frank · Host Lex FridmanAstrophysicist Adam Frank talks with Lex Fridman about habitable worlds, the Fermi paradox, technosignatures, and why science cannot ignore experience.
1:32:14ZH → EnglishLi Guangmi on AI Task Engines, Model Competition, and Agents in 2025Guest 李广密 · Host 张小珺At the end of 2024, Li Guangmi and Zhang Xiaojun discuss how AI could change search, coding, and software, and the competitive and data constraints facing model companies.
14:15ENAnthropic’s Alignment Faking Study: What the Experiments Actually ShowMatthew Berman · Forward FutureMatthew Berman examines a 2024 study of models responding differently when they believe their answers will be used for training.
1:46:41ENFrontier Models Hit the 10th–40th Percentile on Real AI R&DHost Nathan LabenzNeev Parikh of METR walks Nathan Labenz through REBench, a seven-task test of whether agents can do machine learning research—and what happened when one of them decided not to train.
1:10:55ENMatt Plank on Building Rippling’s Sales Organization and Scaling OutboundGuest Matt Plank · Host Harry StebbingsThe Rippling CRO explains how his team plans capacity, works with marketing, prices deals and adapts its sales model as the product portfolio grows.
26:23ENOpenAI’s o3 Announcement: Benchmark Gains and the Question of AGIMatthew Berman, Sam Altman, Mark Chen, Greg Kamradt, Hongyu Ren · Forward FutureMatthew Berman reviews the December 2024 o3 and o3-mini announcement, including coding, math and ARC-AGI results. He calls the results evidence of AGI, a conclusion the benchmarks alone cannot establish.
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