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53:44EN
Sequoia Capital· 18 ago 2026PódcastThe Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.
38:45ENSequoia Capital· 16 jun 2026PódcastThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
2:06:16ZH
Zhang Xiaojun Podcast· 28 nov 2025Pódcast · 2 voces谭捷：机器人通用智能的瓶颈在数据，通用形态仍需时间Invitado: 谭捷 · Presenta: 张小珺Google DeepMind 机器人研究科学家谭捷回顾了从计算机图形学到机器人、从强化学习到 Gemini Robotics 的研究路径。他认为机器人基础模型尚未成为独立学科，数据规模与覆盖度、跨本体迁移、实时推理和安全仍是走向真实应用的关键。
41:36ENSequoia Capital· 18 nov 2025PódcastFour Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.
32:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 24 jul 2025Pódcast · 2 vocesA Hundred People, a Billion in Revenue, and Zero Venture MoneyPresenta: Sarah Guo, Elad GilSurge AI founder Edwin Chen on why quality human data is a poetry problem, not a bounding-box problem, and why leaderboards keep training models to write clickbait.
45:21ENNo Priors: AI, Machine Learning, Tech, & Startups· 17 jun 2025Pódcast · 2 vocesApplied Intuition Is Worth $15 Billion, Hasn't Spent Its Capital, and Wants to Be the OS for Cars and TanksPresenta: Sarah Guo, Elad GilOn No Priors, Qasar Younis and Peter Ludwig explain the Microsoft playbook for vehicles, why they waited for autonomy techniques to converge, and why Waymo's business model is the question that follows the demo.
38:25ENSequoia Capital· 27 may 2025PódcastA thousand airplanes will never train an AI engineerFormer Airbus CTO Paul Eremenko explains why physical-world engineering still has no coding-AI moment, and how P-1 AI's agent Archie is supposed to get there anyway.
55:40ENSequoia Capital· 29 abr 2025PódcastTo Solve All Diseases, Isomorphic Labs Needs a Half-Dozen AlphaFoldsMax Jaderberg on turning DeepMind's game-playing research into a general AI engine for drug design—and why prediction alone cannot search a 10^60 molecular universe.
51:08EN
Unsupervised Learning: With Jacob Effron· 15 abr 2025PódcastThe Transformer Co-Author Who Says Scaling Hit a WallPresenta: Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.
52:30ENSequoia Capital· 28 ene 2025PódcastMove 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2 oct 2024Pódcast30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually ThinkPresenta: Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.
39:45ENSequoia Capital· 24 sept 2024PódcastHarmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.
44:16ENNo Priors: AI, Machine Learning, Tech, & Startups· 5 sept 2024Pódcast · 2 vocesA perfect demo is ten years from a product you can pay forPresenta: Sarah Guo, Elad GilAndrej Karpathy uses Waymo's decade-long gap, Tesla's software bet, and a new AI course to argue that autonomous intelligence will stall at product and globalization, not at the first impressive clip.
39:00ENNo Priors: AI, Machine Learning, Tech, & Startups· 22 may 2024Pódcast · 2 vocesJPMorgan Has 150 Petabytes. GPT-4 Trained on Less Than One.Presenta: Sarah Guo, Elad GilScale AI founder Alexandr Wang tells No Priors why easy internet data is exhausted, why expert-plus-model teams still win, and why the path to AGI looks more like curing cancer than inventing a vaccine.
1:01:39ENCognitive Revolution "How AI Changes Everything"· 13 abr 2024PódcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Presenta: Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.
1:21:50ENCognitive Revolution "How AI Changes Everything"· 14 nov 2023PódcastA 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.Presenta: Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.
1:17:09ENCognitive Revolution "How AI Changes Everything"· 26 sept 2023PódcastGPT-4 as Teacher, GPT-3.5 as Student: A Nine-Tenths Cost Cut and an AI Bundle Nobody Will StartPresenta: Nathan LabenzNathan Labenz reports that chain-of-thought traces from GPT-4 train a cheaper, faster 3.5, then argues for flooring the app accelerator, tapping the brake on GPT-5, and bundling a hundred AI tools for a hundred dollars.
3:11:35EN
Lex Fridman· 21 jun 2023Pódcast · 2 vocesSearch was always a hack: Marc Andreessen on AI, truth, and the next internetInvitado: Marc Andreessen · Presenta: Lex FridmanLex Fridman sits down with the Mosaic co-creator and Andreessen Horowitz founder to ask whether Google Search, the browser, and open-source AI survive the decade.
2:00:19ENCognitive Revolution "How AI Changes Everything"· 6 jun 2023Pódcast1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2Presenta: Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…
1:14:34EN
Lenny's PodcastPódcast · 2 vocesInside the Frontier Lab: How Karina Nguyen Builds Products by Training the ModelInvitado: Karina Nguyen · Presenta: Lenny RachitskyOpenAI researcher Karina Nguyen explains synthetic data, evals, how Canvas and Tasks were made, and which human skills matter as models get smarter.