Recently updated channels

Pick one to see only that channelBrowse all channels →

Results

248 articles
Sort
3 slides15:45EN
MBMatthew Berman· Apr 18, 2025AI 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.Models & trainingAI cost & performanceAgents
58:11EN
Sequoia Capital· Apr 15, 2025PodcastPatrick 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.Models & trainingAI for sciencePretraining & midtraining+3
2:29:41ZH → English
Zhang Xiaojun Podcast· Apr 7, 2025Podcast · 4 speakersChen Jianyu: How Robot Foundation Models Can Become General-Purpose VLA SystemsGuest 陈建宇 · Host 张小珺From SayCan and RT-2 to Diffusion Policy, Tsinghua assistant professor and Epoch Robotics founder Chen Jianyu traces the path from borrowing language models to end-to-end VLA. The hard problems remain diverse data, cross-embodiment generalization, and high-frequency action control.RoboticsModels & trainingMultimodal AI+2
1:14:11EN
Cognitive Revolution "How AI Changes Everything"· Apr 5, 2025PodcastThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGIHost 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.Models & trainingReasoning & test-time computeReinforcement Learning+3
5 slides26:05EN
MBMatthew Berman· Mar 31, 2025Inside 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.AI researchModels & trainingAI Safety+1
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· Mar 23, 2025PodcastA Year to Grow a Brain Organoid, an Hour to Simulate ItHost 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.Models & trainingAI for scienceComputational Biology+3
35:14EN
No Priors: AI, Machine Learning, Tech, & Startups· Mar 20, 2025Podcast · 2 speakersRobots Have No Wikipedia. Chelsea Finn Is Starting With Three Buildings.Host 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.Models & trainingRoboticsData quality & curation+3
1:10:23EN
Unsupervised Learning: With Jacob Effron· Mar 17, 2025PodcastA Million Tokens per Dollar: Why Noam Shazeer Thinks Inference Compute Is Still UntappedHost 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.Models & trainingReasoning & test-time computeScaling Laws+3
1:56:38EN
Cognitive Revolution "How AI Changes Everything"· Mar 8, 2025Podcasto3 took ARC from 20% to 87%. Nathan Labenz sketches early superintelligenceHost 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.Models & trainingReinforcement LearningDistributed training & inference+3
1:02:41EN
20VC with Harry Stebbings· Mar 3, 2025Podcast · 2 speakersMike Krieger on AI Products, Model Competition and the Future of CodingGuest Mike Krieger · Host Harry StebbingsAnthropic’s chief product officer explains how he thinks about product design, model differentiation and the limits of current AI tools.AI StrategyProduct StrategyModels & training+2
57:41EN
No Priors: AI, Machine Learning, Tech, & Startups· Feb 25, 2025Podcast · 2 speakersA Hundred Million Cells, Four People, Three Days: Biology's ImageNet MomentHost 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.Models & trainingAI for scienceData quality & curation+3
1:18:09EN
20VC with Harry Stebbings· Feb 24, 2025Podcast · 2 speakersSteeve Morin on AI Inference, Chips and the Cost of Switching HardwareGuest Steeve Morin · Host Harry StebbingsThe ZML founder explains the difference between training and production inference and offers a competitive view of the AI hardware market.Infrastructure & deploymentInferenceAI cost & performance+2
2:36:13ZH → English
Zhang Xiaojun Podcast· Feb 24, 2025Podcast · 2 speakersSonglin Yang on New Attention Papers from DeepSeek, Kimi, and MiniMaxGuest Songlin Yang(松琳) · Host 张小珺From dynamic sparse attention to hybrid linear-attention architectures: how three approaches to long context balance training, inference, and hardware efficiency.Transformers & attentionGPU programming & kernelsModels & training+2
1:25:52EN
20VC with Harry Stebbings· Feb 17, 2025Podcast · 2 speakersJonathan Ross on Groq, Inference Economics and the AI Infrastructure RaceGuest Jonathan Ross · Host 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.Infrastructure & deploymentModels & trainingAI cost & performance+2
22:32EN
No Priors: AI, Machine Learning, Tech, & Startups· Feb 7, 2025Podcast · 2 speakersThe $5.5 Million Was Only the Last MileHost 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.Models & trainingAI StrategyAI cost & performance+3
2:49:35ZH → English
Zhang Xiaojun Podcast· Feb 4, 2025Podcast · 2 speakersPan Jiayi on R1, o1, and Kimi K1.5: How Reinforcement Learning Teaches Models to ReasonGuest 潘嘉怡 · Host 张小珺Pan Jiayi, a Berkeley PhD student, walks through reasoning-model reports from DeepSeek, OpenAI, and Kimi, unpacking long chains of thought, GRPO, reward design, and distillation. R1-Zero’s “aha moment” shows how reasoning strategies can emerge through reinforcement learning.Reinforcement LearningModels & trainingAI research+2
1:50EN
MBMatthew Berman· Jan 30, 2025Five AI Trends Discussed by Coveo’s Sébastien PaquetMatthew Berman · Forward FutureMatthew Berman summarizes a 2025 interview on production systems, smaller models, agents and trust.Enterprise AIAgentsModels & training+1
1:48:20EN
Cognitive Revolution "How AI Changes Everything"· Jan 25, 2025PodcastFrom 15% to 70% on Right-or-Wrong Scores: DeepSeek-R1 Laid Reinforcement Learning's Cards on the TableHost 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.Models & trainingReinforcement LearningReasoning & test-time compute+3
1:40:22EN
Cognitive Revolution "How AI Changes Everything"· Jan 22, 2025PodcastTwenty-atom crystals taught an AI the physics of a heartbeatHost 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.Models & trainingAI for scienceML fundamentals+3
2:04:45EN
Cognitive Revolution "How AI Changes Everything"· Jan 7, 2025Podcasto3 Hit Superhuman on ARC-AGI. It Still Lost at Tic-Tac-ToeHost 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.Models & trainingReasoning & test-time computeBenchmarks+3
2 slides30:29EN
MBMatthew Berman· Jan 3, 2025How 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.Reinforcement LearningModels & trainingAI research+1
1:27:13ZH
Zhang Xiaojun Podcast· Dec 29, 2024Podcast · 2 speakers李想:汽车将从交通工具进化为空间机器人Guest 李想 · Host 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。AI StrategyProduct StrategyAutonomous Driving+2
1:07:32EN
Unsupervised Learning: With Jacob Effron· Dec 18, 2024Podcasto1 Is a New Generation — and the Day AGI Arrives Will Feel BoringHost 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.Models & trainingReasoning & test-time computeAgent engineering+3
48:18EN
Unsupervised Learning: With Jacob Effron· Dec 6, 2024PodcastNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomHost Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.Models & trainingReasoning & test-time computeAGI+3
Load moreShowing 24 of 248