筛选结果
26 篇排序
56:31EN
Unsupervised Learning: With Jacob Effron· 2026年10月6日播客Post-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab主持 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日播客The Periodic Table Was Already in the Weights主持 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日播客The GPT moment for video hasn’t arrived, but AGI may already be here主持 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日播客 · 2 人对谈Inference Is the Last Market: Baseten’s 30x Year主持 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日播客The reward jumped from 3 to 180. Every Hacker News title was a Google layoff.主持 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日播客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日播客The Architecture Barely Changed. Data, Cost, and Open Weights Did.主持 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日播客The Summer GPT-5 Disappointed Does Not Mean AI Progress Has Stalled主持 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日播客 · 2 人对谈STaR's Author Wants Models With EQ, Not Just More IQ主持 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日播客ChatGPT's Co-Creator Left to Put Nature in the Reward Loop主持 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日播客Plus Five for Format, Plus Ten if It Compiles主持 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日播客Every Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goes主持 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日播客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日播客An Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a Decade主持 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日播客DeepSeek's $5 million training claim and the five-year bet on compute主持 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日播客A Team of Fifteen Matched Meta’s Post-Training on Meta’s Own Base主持 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日播客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日播客Claude Was Trained to Deny Inner Life. After a Long Talk, It Said It Has One主持 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日播客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日播客 · 2 人对谈JPMorgan Has 150 Petabytes. GPT-4 Trained on Less Than One.主持 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日播客The AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understand主持 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日播客 · 2 人对谈GPT-4 is a very early AI. ChatGPT is the line in the history books嘉宾 Sam Altman · 主持 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播客From RAG to Reasoning: Why the Future of AI Is a System, Not a Model主持 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 → 简体中文
Lenny's Podcast播客 · 2 人对谈从制品到有机体：微软Asha Sharma谈会学习的产品和智能体社会嘉宾 Asha Sharma · 主持 Lenny Rachitsky微软AI平台产品负责人解释，为什么产品正变成靠后训练持续进化的活系统，界面如何走向代码与可组合性，以及智能体怎样改写组织图。加载更多已显示 24 篇，共 26 篇