Artículos recientes
4172 artículosOrdenar
1:59:55ENMost People Would Quit Tomorrow: Nathan Labenz Maps AI Utopia and DoomPresenta: Nathan LabenzIn part two of a Cognitive Revolution AMA, Nathan Labenz answers listener questions on abundance, superintelligence, p(doom), machine consciousness, and what to do this week.
32:29ENNVIDIA at CES 2025: AI Agents, Cosmos and Project DIGITSMatthew Berman, Jensen Huang · Forward FutureMatthew Berman examines Jensen Huang’s keynote, from neural graphics and AI scaling to a desktop system for local model development.
1:06:04ENDan Gill on Carvana’s Unit Economics, Product Decisions and TurnaroundInvitado: Dan Gill · Presenta: 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-ToePresenta: 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 SellInvitado: Mike Maples · Presenta: 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 PeaceInvitado: Volodymyr Zelenskyy · Presenta: 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-4oPresenta: 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李想:汽车将从交通工具进化为空间机器人Invitado: 李想 · Presenta: 张小珺理想汽车 CEO 李想谈公司为何从造车走向人工智能:基座模型是 AI 时代的操作系统,汽车是进入物理世界的重要载体。对他而言,技术路线最终要落实为更好的用户体验、能力与长期价值。
1:57:00ENLess Than 1%: Why OpenAI's roon Thinks the Good Guys Get AGI FirstPresenta: 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 centerPresenta: 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 EveryonePresenta: 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 CivilizationInvitado: Adam Frank · Presenta: Lex FridmanAstrophysicist Adam Frank talks with Lex Fridman about habitable worlds, the Fermi paradox, technosignatures, and why science cannot ignore experience.
1:32:14ZH李广密:AI 任务引擎、模型竞争与 2025 年的 Agent 预测Invitado: 李广密 · Presenta: 张小珺在 2024 年末,李广密与张小珺讨论 AI 如何改变搜索、编程和软件,以及模型公司面临的竞争与数据约束。
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&DPresenta: 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.
Cargar másMostrando 24 de 4172









