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35:39ENCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That RatioPresenta: Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
2:25:58ENAGI Is Already Here. Building NVIDIA Is Not.Invitado: Jensen Huang · Presenta: Lex FridmanLex Fridman sits down with Jensen Huang for two and a half hours on extreme co-design, CUDA, four scaling laws, and why a $1 billion AI company is easier than a durable one.
39:16EN500 Gloves, 10 Million Trajectories, and a $10,000 Home RobotPresenta: Sarah Guo, Elad GilSunday Robotics co-founders Tony Zhao and Cheng Chi map the gap between a scalable imitation-learning recipe and a machine that actually does the dishes.
1:48:46ZH刘先明:拆掉语言,让物理 AI 回到数据与动作Invitado: 刘先明 · Presenta: 张小珺小鹏自动驾驶中心负责人刘先明解释,为什么 VLA 训练中间的语言监督会成为效率瓶颈,以及他如何推动小鹏从自动驾驶团队转向物理 AI。访谈也谈到规模化数据、组织变革、量产安全与自动驾驶的下一阶段。
1:09ENA Discussion of GPT-4.5’s Scaling and TrainingA speaker offers an assessment of GPT-4.5’s cost, speed and alleged training challenges.
2:12:04ENFrom a Five-Year Phone Queue to 480 Trillion Tokens a MonthInvitado: Sundar Pichai · Presenta: Lex FridmanSundar Pichai talks with Lex Fridman about Chennai, the AI package, Search, Chrome, Waymo, and why he stayed calm when the headlines said Google was finished.
57:41ENA Hundred Million Cells, Four People, Three Days: Biology's ImageNet MomentPresenta: Sarah Guo, Elad GilVevo Therapeutics and the Arc Institute open-sourced Tahoe-100M and a 230-million-cell atlas in the same week — and argued that virtual cells, not just protein folders, are the next language model of biology.
21:10ENSam Altman’s 2025 AI Coding Forecast and Three ObservationsMatthew Berman, Sam Altman · Forward FutureMatthew Berman examines predictions about reasoning models, software agents and AI economics, distinguishing competitive-programming results from broader work.
44:16ENCohere's Aidan Gomez: The Model Curve Is Flattening, and $20 Million Now Buys GPT-4Presenta: Sarah Guo, Elad GilThe Attention Is All You Need co-author tells No Priors why enterprises should stop waiting for the next model and start putting today's models into production.
5:15:00ENDario Amodei Has Seen This Scaling Movie Enough TimesInvitado: Dario Amodei · Presenta: Lex FridmanAnthropic’s CEO puts numbers on frontier training costs and AGI, then hands the mic to the people who shape Claude’s character and look inside its weights.
36:49ENJensen Huang: NVIDIA Is No Longer Building Computers. It Is Building AI FactoriesPresenta: Sarah Guo, Elad GilOn No Priors, NVIDIA’s CEO walks through hyper Moore’s law, NVLink, a 100,000-GPU cluster stood up in weeks, and why tokens are the new commodity.
44:16ENA 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.
50:20ENArvind Narayanan on AI Scaling, Real-World Risks and the Limits of Model BenchmarksInvitado: Arvind Narayanan · Presenta: Harry StebbingsThe Princeton professor challenges simple claims about scaling, AGI timelines and AI adoption while discussing deepfakes, healthcare, education and security.
42:42ENEthereum Once Held Two Thousand GPT-3 Clusters of GPUsPresenta: Sarah Guo, Elad GilFoundry CEO Jared Quincy Davis on idle H100s, why today's AI cloud is still colocation, and how compound systems move work off giant interconnected clusters.
1:33:07ZH广密复盘全球大模型这一年:Scaling Law、AGI 豪赌与中美格局Invitado: 李广密 · Presenta: 张小珺拾象创始人李广密从硅谷一线观察出发,回顾 OpenAI、Anthropic、Google 与中国模型公司的竞争。他认为,模型能力与成本共同决定新一轮应用爆发,而巨额投入押注的是智能能否持续扩展以及 AI 对经济和产业的长期重构。
46:09ENOriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are NumberedPresenta: Sarah Guo, Elad GilGoogle DeepMind’s VP of research on Gemini, long context, the coming shift from pretraining to RL, and why AGI may never have a finish line.
29:09ENThe Hyperscalers Are Spending $200 Billion — and the Next Bottleneck Is a Power PlantPresenta: Sarah Guo, Elad GilSarah Guo and Elad Gil walk through music models, on-device LLMs, long context, and why AI capex now sits beside oil and broadband.
31:24ENSora's Leads: A Minute of HD Video Is Just the GPT-1 of Video ModelsPresenta: Sarah Guo, Elad GilAditya Ramesh, Tim Brooks, and Bill Peebles tell No Priors why text-to-video sits on the path to AGI, why they started from scratch instead of extending an image generator, and why they still have no product date.
40:58EN99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses FirstPresenta: Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.
32:57ENA 7-billion-parameter model on a MacBook: Mistral's CEO reruns the cost of AIPresenta: Sarah Guo, Elad GilArthur Mensch tells No Priors why Chinchilla made small models valuable, why open-sourcing Mistral 7B is not a bioweapon risk, and why guardrails belong on the application.
41:58ENReliability is the bottleneck. Autonomy is what would make AI feel alive.Presenta: Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.
30:03ENA Dinner-Plate Chip Cut Training From 60 Days to 3.5Presenta: Sarah Guo, Elad GilCerebras CEO Andrew Feldman tells No Priors why wafer-scale silicon, not another GPU, is the answer to the compute crunch — and why most production models will stay at 13 billion parameters or below.
40:25ENA 6-Billion-Parameter Clone of ChatGPT’s Core TrickPresenta: Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.
45:03ENEmad Mostaque’s bet: open small models, not one giant brainPresenta: Sarah Guo, Elad GilStability AI’s founder tells No Priors why foundation models should be public infrastructure, why small models can beat giant ones, and what that means for media, medicine, and AGI.
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