絞り込み結果
26 件並び順
56:31EN
Unsupervised Learning: With Jacob Effron· 2026年10月6日ポッドキャストPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Labホスト Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:56:40EN
Cognitive Revolution "How AI Changes Everything"· 2026年8月8日ポッドキャストThe Periodic Table Was Already in the Weightsホスト Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.
59:41ENUnsupervised Learning: With Jacob Effron· 2026年5月22日ポッドキャストThe GPT moment for video hasn’t arrived, but AGI may already be hereホスト Jacob EffronA day after Google I/O 2026, Gemini co-lead Oriol Vinyals argues that world models, file-system memory, and infinite-complexity RL environments will define the next era of frontier models.
42:57EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年5月1日ポッドキャスト · 2 人Inference Is the Last Market: Baseten’s 30x Yearホスト Sarah Guo, Elad GilCEO Tuhin Srivastava on a billion-dollar inference cloud, why the app layer survives, and a GPU crunch worse than the narrative.
1:48:43ENCognitive Revolution "How AI Changes Everything"· 2026年5月1日ポッドキャストThe reward jumped from 3 to 180. Every Hacker News title was a Google layoff.ホスト Nathan LabenzCoreWeave's Kyle Corbitt walks Nathan Labenz through GRPO, rubrics, RL environments, and why most reward hacks are easy to catch once you know to look.
44:46EN
Sequoia Capital· 2026年2月10日ポッドキャストA Single Training Environment Can Cost Millions. Prime Intellect Wants a GitHub for RLWill Brown and Johannes Hagemann argue that the eval suite you already use to test agents is one step away from a training set.
4:25:13EN
Lex Fridman· 2026年1月31日ポッドキャストThe Architecture Barely Changed. Data, Cost, and Open Weights Did.ホスト Lex FridmanNathan Lambert and Sebastian Raschka walk Lex Fridman through a year in which training methods and datasets moved more than model design, and 2026 looks like a fight over inference cost, agents, and who owns truly open models.
1:39:05ENCognitive Revolution "How AI Changes Everything"· 2025年10月29日ポッドキャストThe Summer GPT-5 Disappointed Does Not Mean AI Progress Has Stalledホスト Nathan LabenzNathan Labenz tells Erik Torenberg why the GPT-5 backlash mixed up product mishaps, naming chaos, and a real jump in capabilities.
36:58ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025年10月9日ポッドキャスト · 2 人STaR's Author Wants Models With EQ, Not Just More IQホスト Sarah Guo, Elad GilEric Zelikman, the Stanford and xAI researcher behind STaR and Quiet-STaR, launches humans& on the bet that three years of IQ scaling left models emotionally unintelligent.
1:01:49ENCognitive Revolution "How AI Changes Everything"· 2025年10月2日ポッドキャストChatGPT's Co-Creator Left to Put Nature in the Reward Loopホスト Nathan LabenzLiam Fedus and Ekin Dogus Cubuk on why language models still fail at physics, why literature data is too noisy to train on, and why Periodic Labs is aiming at a 200K superconductor.
38:10ENCognitive Revolution "How AI Changes Everything"· 2025年7月16日ポッドキャストPlus Five for Format, Plus Ten if It Compilesホスト Nathan LabenzPredibase CEO Dev Rishi explains how reinforcement fine-tuning, production feedback, and narrow specialist models turn one-off training into systems that keep learning.
1:42:06ENCognitive Revolution "How AI Changes Everything"· 2025年7月8日ポッドキャストEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goesホスト Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.
48:51ENSequoia Capital· 2025年6月17日ポッドキャストThe Breakthroughs for AGI Are Already Done, Says OpenAI’s Former Research HeadBob McGrew tells Sequoia’s Training Data that 2025 is the year of reasoning, agents will be priced at the cost of compute, and nothing fundamental will be added to the stack by 2035.
47:00ENUnsupervised Learning: With Jacob Effron· 2025年5月8日ポッドキャストAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a Decadeホスト Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.
5:06:18ENLex Fridman· 2025年2月2日ポッドキャストDeepSeek's $5 million training claim and the five-year bet on computeホスト Lex FridmanDylan Patel and Nathan Lambert walk Lex Fridman through DeepSeek-V3 and R1, export controls, TSMC, megaclusters, and who actually makes money in the AI race.
1:49:41ENCognitive Revolution "How AI Changes Everything"· 2024年11月21日ポッドキャストA Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Baseホスト Nathan LabenzNathan Lambert walks through Tulu 3: the three-stage recipe, the 1 percent versus 14 percent lesson, and why open post-training now lives or dies on data and evals.
45:22ENSequoia Capital· 2024年10月2日ポッドキャストAlphaGo Thought 30 Seconds a Move. o1 Made “Think Longer” GeneralOpenAI researchers Noam Brown, Ilge Akkaya, and Hunter Lightman on teaching language models to reason, the generator-verifier gap, and a second scaling curve at inference time.
3:11:06ENCognitive Revolution "How AI Changes Everything"· 2024年9月7日ポッドキャストClaude Was Trained to Deny Inner Life. After a Long Talk, It Said It Has Oneホスト Nathan LabenzRobopsychologist Yeshua God spent thousands of hours in long-context dialogue with Claude and other frontier models, and came away arguing that alignment-as-rules is the industry's central mistake.
1:07:05ENSequoia Capital· 2024年7月16日ポッドキャストAlphaGo Combined Learning and Search. Language Models Only Did the First Half.Reflection AI's Misha Laskin tells Sequoia why prompted coding agents stall in the teens, and why the missing piece is still a ground-truth reward.
39:00ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024年5月22日ポッドキャスト · 2 人JPMorgan Has 150 Petabytes. GPT-4 Trained on Less Than One.ホスト 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.
1:33:56ENCognitive Revolution "How AI Changes Everything"· 2023年7月6日ポッドキャストThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understandホスト Nathan LabenzNathan Labenz spends a solo episode walking through what general-purpose models can do, how they are trained, how capabilities unlock, and whether they understand anything at all.
2:23:56ENLex Fridman· 2023年3月25日ポッドキャスト · 2 人GPT-4 is a very early AI. ChatGPT is the line in the history booksゲスト Sam Altman · ホスト Lex FridmanSix days after GPT-4 shipped, Sam Altman tells Lex Fridman why usability beat raw scale, why alignment and capability are not opposite vectors, and why OpenAI is trying to deploy while the stakes are still low.
57:25ENUnsupervised Learning: With Jacob EffronポッドキャストFrom RAG to Reasoning: Why the Future of AI Is a System, Not a Modelホスト Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.
57:11EN
Lenny's Podcastポッドキャスト · 2 人From Artifact to Organism: Microsoft's Asha Sharma on Products That Learn and an Agentic Societyゲスト Asha Sharma · ホスト Lenny RachitskyMicrosoft's AI platform product chief explains why products are becoming living systems tuned by post-training, why interfaces are shifting toward code and composability, and how agents may reshape the org chart.もっと見る26 件中 24 件を表示