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38:14ENDiffusion Will Win Inference: Stefano Ermon Bets Parallel Tokens Beat Custom SiliconAnime : Sarah Guo, Elad GilThe Stanford diffusion pioneer tells No Priors why a 50-person lab is training language models that generate many tokens at once — and why that maps to GPUs the way transformers once mapped to training.
3:36:13ENNVIDIA’s Ming-Yu Liu on Cosmos, Physical AI, and Creating New MarketsInvité : Ming-Yu Liu · Anime : 张小珺NVIDIA research VP Ming-Yu Liu explains how a decade of generative-model research led to Cosmos 3, a world foundation model for Physical AI. He also shares what he learned from Jensen Huang about long-term bets, teamwork, and building markets instead of fighting over existing ones.
2:59:03ENYou Kaichao on How vLLM Grew from Open-Source Project to AI Infrastructure CompanyInvité : You Kaichao · Anime : 张小珺Inferact co-founder You Kaichao traces vLLM’s path from Berkeley research to a company, then explains why model, inference, hardware and agent design increasingly have to move together.
3:46:12ENKay Ke on Physical Intelligence, Robot Learning, and the Future of RoboticsInvité : Kay Ke · Anime : 张小珺Physical Intelligence researcher Kay Ke traces the field's research lineages and explains Pi's progression from π₀ to π*₀.₆. She also reflects on education, fiction, ambition, and what it means to build robots that work beyond a demo.
36:19ENThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score ModelsAnime : Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
32:22ENDemis Hassabis on AGI, Scientific Discovery and the Challenges AheadInvité : Demis Hassabis · Anime : Harry StebbingsThe Google DeepMind CEO discusses compute, continual learning, safety standards and his hopes for AI in science, medicine and energy.
59:03ENJoelle Pineau on Scaling, Reinforcement Learning and Enterprise AIInvité : Joelle Pineau · Anime : Harry StebbingsCohere’s chief AI officer discusses research uncertainty, agent security, synthetic data and the difference between benchmarks and useful work.
13:30ENHow AlphaGeometry Combines Logical Proof with Creative ConstructionAleph0Aleph0 explains how a symbolic geometry solver gets surprisingly far without AI, and how a language model supplies the auxiliary constructions that take it to Olympiad level.
47:05ENLogan Kilpatrick on AI Developers, Interfaces, and the Future of ModelsMatthew Berman, Logan Kilpatrick · Forward FutureIn a July 2025 conversation, Google’s Logan Kilpatrick discusses Windsurf, agent interfaces, coding skills, Veo, and the shifting boundary between models and application scaffolding.
42:09ENAlphaEvolve found algorithms humans missed for 50 years — then sped up Gemini 23%Anime : Sarah Guo, Elad GilGoogle DeepMind’s Pushmeet Kohli and Matej Balog tell No Priors how an evolutionary coding agent searches algorithm space the way AlphaGo searched Go.
3:14:34ENIf ten things make a problem hard, Terence Tao turns nine of them offInvité : Terence Tao · Anime : Lex FridmanThe Fields Medalist walks Lex Fridman from the Kakeya needle and Navier-Stokes through Lean, Perelman, and why today's AI still cannot smell a dead-end proof.
38:10ENo3 should wait exactly as long as the answer takesAnime : Sarah Guo, Elad GilOpenAI researchers Eric Mitchell and Brandon McKinzie tell No Priors why o3's leap is a chain of tools during reasoning — and why you should send the same prompt a hundred times.
2:36:13ZH松琳解读 DeepSeek、Kimi 与 MiniMax 的注意力新论文Invité : Songlin Yang(松琳) · Anime : 张小珺从动态稀疏注意力到线性注意力混合架构:三条长上下文路线如何兼顾训练、推理与硬件效率
53:07ZH张亚勤:信息智能、物理智能与生物智能的 AGI 路线图Invité : 张亚勤 · Anime : 张小珺张亚勤把 AGI 的发展分为信息、物理和生物三类智能:信息智能可能在五年内接近人类,通用机器人约需十年,生物智能则可能在二十年后扩展人的记忆与健康。他也讨论大模型如何为自动驾驶和机器人补上数据、常识与行动能力。
45:31ENJerry Chow on Quantum Computing, Encryption, AI and Error CorrectionMatthew Berman, Jerry Chow · Forward FutureIBM’s quantum systems director explains qubits, cryogenic hardware, software and the work needed to make quantum computers useful.
2:49:35ZH潘嘉怡解读 R1、o1 与 Kimi K1.5:强化学习如何教模型学会推理Invité : 潘嘉怡 · Anime : 张小珺伯克利博士生潘嘉怡带读 DeepSeek、OpenAI 与 Kimi 的推理模型报告,拆解长思维链、GRPO、奖励设计与蒸馏。R1-Zero 的“顿悟时刻”展示了推理策略如何在强化学习中涌现。
1:19:00ENEiso Kant on Poolside, Compute and AI for Software DevelopmentInvité : Eiso Kant · Anime : Harry StebbingsPoolside’s CTO explains code-execution feedback, the cost of model development and his company’s ambitions in the AI race.
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Invité : 李广密 · Anime : 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。
34:09ENFive Independent Teams Found the Same 10-to-1 Mix That Beats TransformersAnime : Sarah Guo, Elad GilThe authors of S4 and Mamba argue that mostly state-space layers plus a dash of attention is the architecture that actually works—and they are shipping it first as real-time speech.
26:00ENWhy a Zapier founder thinks AGI research has been stalled for four yearsAnime : Sarah Guo, Elad GilMike Knoop and François Chollet put more than a million dollars on beating ARC-AGI, the eval they say actually measures general intelligence.
2:15:39ENRoman Yampolskiy Puts Superintelligent Ruin at 99.99 PercentInvité : Roman Yampolskiy · Anime : Lex FridmanThe AI safety researcher tells Lex Fridman that controlling AGI is as impossible as a perpetual motion machine, and that tests, open source, and regulation cannot close the gap.
2:50:44ENThe Pirahã Have No Word for OneInvité : Edward Gibson · Anime : Lex FridmanMIT psycholinguist Ted Gibson tells Lex Fridman why related words sit together, why language is not thought, and why large language models ace form while missing meaning.
2:47:17ENIf You Want Human-Level AI, Abandon Generative ModelsInvité : Yann Lecun · Anime : Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.
21:00ENJim Fan's Foundation Agent Vision: Skills, Robot Bodies, and SimulationMatthew Berman, Jim Fan · Forward FutureMatthew Berman examines research on Minecraft agents, varied robot bodies, and simulation as steps toward more general embodied AI.
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