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15:45ENAI News: Gemini 2.5 Flash, OpenAI Models, Claude Research and Kling 2.0Matthew Berman · Forward FutureMatthew Berman reviews a week of 2025 model releases, research tools and agent announcements, including historical price and benchmark comparisons.
58:11ENPatrick Hsu Wants an App Store for Biology, Not Just Better DrugsThe Arc Institute co-founder argues that Evo 2, trained on genomes rather than proteins, should underpin tools for every step of the scientific method.
2:29:41ZH陈建宇:机器人基座模型如何走向通用 VLAInvitado: 陈建宇 · Presenta: 张小珺从 SayCan、RT-2 到 Diffusion Policy,清华助理教授、星动纪元创始人陈建宇梳理机器人模型从借用语言模型到端到端 VLA 的路线。关键难题仍是多样化数据、跨本体泛化和高频动作控制。
1:14:11ENThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIPresenta: Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.
26:05ENInside Claude: What Interpretability Research Reveals—and What It Cannot Yet ExplainMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s case studies on multilingual features, planning, arithmetic, hallucinations and safety.
1:43:54ENA Year to Grow a Brain Organoid, an Hour to Simulate ItPresenta: Nathan LabenzStanford postdoc Siyu He tells Nathan Labenz how Squidiff and CORAL move single-cell and spatial experiments into the computer — and where the models still cannot go.
35:14ENRobots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.Presenta: Sarah Guo, Elad GilPhysical Intelligence’s cofounder tells No Priors why a generalist robot model has to be trained across embodiments, why open-sourcing hardware is a bet against the problem going unsolved, and why humanoids are a little overrated.
1:10:23ENA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still UntappedPresenta: Jacob EffronThe Transformer co-inventor and Gemini researcher Jack Rae walk through test-time compute, Ilya Sutskever's AGI critique, and a four-year-old who now lectures his teacher about lizards.
1:56:38ENo3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligencePresenta: Nathan LabenzOn Consistently Candid, the Cognitive Revolution host argues that math and coding will be superhuman by 2026, and that a reasoning core plus specialist “intuitive physics” may already be enough.
1:02:41ENMike Krieger on AI Products, Model Competition and the Future of CodingInvitado: Mike Krieger · Presenta: Harry StebbingsAnthropic’s chief product officer explains how he thinks about product design, model differentiation and the limits of current AI tools.
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.
1:18:09ENSteeve Morin on AI Inference, Chips and the Cost of Switching HardwareInvitado: Steeve Morin · Presenta: Harry StebbingsThe ZML founder explains the difference between training and production inference and offers a competitive view of the AI hardware market.
2:36:13ZH松琳解读 DeepSeek、Kimi 与 MiniMax 的注意力新论文Invitado: Songlin Yang(松琳) · Presenta: 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
1:25:52ENJonathan Ross on Groq, Inference Economics and the AI Infrastructure RaceInvitado: Jonathan Ross · Presenta: Harry StebbingsThe Groq CEO explains his bet on inference chips, compares his company’s architecture with GPUs, and discusses the financing and power needed to scale.
22:32ENThe $5.5 Million Was Only the Last MilePresenta: Sarah Guo, Elad GilOn No Priors' 100th episode, Sarah Guo and Elad Gil separate DeepSeek's paper cost from the compute behind it, then walk through OpenAI's Deep Research, Stargate, and their bets for 2025.
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Invitado: 潘嘉怡 · Presenta: 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。
1:50ENFive AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.
1:48:20ENFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the TablePresenta: Nathan LabenzOn Inauguration Day 2025, DeepSeek and Moonshot dropped reasoning-model results that Nathan Labenz reads as proof the reinforcement-learning recipe is simple, public, and still climbing.
1:40:22ENTwenty-atom crystals taught an AI the physics of a heartbeatPresenta: Nathan LabenzOrbital Materials' Jonathan Godwin and Tim Duignan tell Nathan Labenz how a neural network trained on tiny crystals simulated a potassium ion channel on a single 2017 GPU.
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.
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.
1:27:13ZH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。
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel BoringPresenta: Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.
48:18ENNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomPresenta: Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
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