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2:59:44EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2026年6月3日播客两门濒危语言难倒了 Transformer,嵌套学习给模型加上“睡眠”按钮主持 Nathan LabenzGoogle 研究员 Ali Behrouz 向 Nathan Labenz 讲解,语言模型要获得真正的持续学习,不能只堆叠层数,还要堆叠更新频率,并加入一个离线的睡眠阶段。模型与训练Continual learningTransformers & attention+3
1:01:14EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2026年5月20日播客模型吞掉脚手架:谷歌如何计划把智能体推向各处主持 Nathan Labenz泄露的“没有护城河”备忘录发布三年之后,DeepMind 的 Gemini 负责人带我们了解 3.5 Flash、Omni,以及如今贯穿谷歌各项产品的共享智能体(Agent)框架(harness)。企业与战略智能体工程Distillation+3
44:34EN → 简体中文
Unsupervised Learning: With Jacob Effron· 2025年2月19日播客智能越便宜,我们买得越多主持 Jacob Effron亚马逊通用人工智能(AGI)实验室负责人 David Luan 谈 DeepSeek 真正意味着什么、为什么下一 Token 预测还不够,以及为什么智能体(Agent)在可靠性上仍然卡壳。智能体智能体工程Reinforcement Learning+3
26:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年9月12日播客 · 2 人对谈API prices fell 200x. The LLM table still is not set.主持 Sarah Guo, Elad GilSarah Guo and Elad Gil, with no guest this week, argue over whether the language-model market has already consolidated — and why falling prices, five-person labs, and AMD’s shopping spree all cut against a simple ending.企业与战略AI StrategyPricing Strategy+3
42:08EN
Sequoia Capital· 2024年7月30日播客Meta Trained a 405B Teacher on 16,000 GPUs — Then Told the World to Distill ItTwo days after Llama 3.1 405B shipped, Meta's generative-AI product lead walks Sequoia through why the most expensive model in the family is free, and why he thinks the frontier itself is heading toward commodity.开源与社区Open-weight modelsDistillation+3
1:12:15EN
Unsupervised Learning: With Jacob Effron播客The Open-Model Vibe Check: China, Containment, and the Data Moat主持 Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.开源与社区Open-weight modelsOpen-source ecosystems+3
1:13:40EN
Unsupervised Learning: With Jacob Effron播客The Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Moment主持 Jacob EffronVincent, a distinguished engineer at Waymo, explains how foundation models became teachers for self-driving, why the long tail and causality are the real frontier, and where robotics still lacks its generalist proof point.Autonomous DrivingRoboticsMultimodal AI+3