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248 篇
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1:56:35EN
Cognitive Revolution "How AI Changes Everything"播客From Autocomplete to Alien Optimizer: Riley Goodside on Three Eras of Prompting主持 Nathan LabenzScale AI's first staff prompt engineer traces how language models went from pure text prediction to instruction following to RLHF, and what that means for building with them.模型与训练Prompting & in-context learningPrompt injection+2
1:07:29EN
Lex Fridman播客Deep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZero主持 Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.模型与训练Reinforcement LearningDeep Learning+3
24:22EN
Lex Fridman播客 · 2 人对谈Craftsmanship, First Principles and the Road to Self-Driving: Jim Keller on Working with Elon Musk嘉宾 Jim Keller · 主持 Lex FridmanThe veteran chip architect explains why he thinks autonomous driving is a tractable engineering problem, how Tesla's cost constraints shaped its hardware, and what he took from Musk's way of thinking.模型与训练Autonomous DrivingAutonomous Systems+3
9:59EN
Lex Fridman播客Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning主持 Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.模型与训练机器学习基础Deep Learning+3
15:01EN
Lex Fridman播客 · 2 人对谈Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks嘉宾 Daniel Kahneman · 主持 Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.模型与训练Deep LearningAI research+3
56:20EN
No Priors: AI, Machine Learning, Tech, & Startups播客 · 2 人对谈Biohub's Bet: Building Open AI World Models of Biology From Proteins Up to Cells主持 Sarah Guo, Elad GilMark Zuckerberg, Priscilla Chan and Alex Rives explain why Biohub pairs a frontier AI lab with frontier wet-lab biology, and why it releases tools like ESMFold2 as open source.模型与训练AI for scienceOpen-source ecosystems+3
1:25:16EN
Lex Fridman播客From Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional Networks主持 Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.模型与训练Deep LearningComputer Vision+3
1:28:53EN
Lex Fridman播客 · 2 人对谈Machine Learning for Business Students: Powerful, Narrow, and Easier to Fool Than You Think嘉宾 MIT Sloan · 主持 Lex FridmanLex Fridman's non-technical MIT Sloan lecture explains how machine learning works, why it is so capable at perception, and where it still breaks in the real world.模型与训练机器学习基础AI Strategy+3
11:11EN
Lex Fridman播客 · 2 人对谈Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General嘉宾 Yann Lecun · 主持 Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.模型与训练Benchmarks通用人工智能+3
1:24:43EN
Lex Fridman播客From Sparse Coding to GANs: A Tour of Unsupervised Deep Learning in 2016主持 Lex FridmanRuslan Salakhutdinov walks through autoencoders, Boltzmann machines, variational autoencoders and adversarial networks at the Deep Learning School, with candid notes on what did and did not work.模型与训练Deep Learning机器学习基础
1:17:38EN
Lex Fridman播客 · 2 人对谈Brains Are Body Regulators: Lisa Feldman Barrett on Why Emotions Are Constructed, Not Detected嘉宾 Lisa Feldman Barrett · 主持 Lex FridmanIn a guest talk for MIT's AGI course, neuroscientist Lisa Feldman Barrett explains why faces don't display emotions, why brains exist to run bodies, and what that means for building human-like AI.模型与训练Neuroscience & AI通用人工智能+3
58:46EN
Lex Fridman播客Caging the Neural Network: How Aptiv Thinks About Safe Self-Driving主持 Lex FridmanAptiv Autonomous Mobility's Karl Iagnemma and Oscar Beijbom explain why end-to-end learning is hard to trust in cars, and show how PointPillars and nuScenes push lidar perception forward.模型与训练Autonomous DrivingDeep Learning+3
1:23:18EN
Cognitive Revolution "How AI Changes Everything"播客From GPT-2 to GPT-3 Moments in Robotics: Six DeepMind Papers on Bridging Robots and the Internet主持 Nathan LabenzKeerthana Gopalakrishnan and Ted Xiao walk through RT-2, RT-X, RT-Trajectory, AutoRT, Learning to Learn Faster and PIVOT, and say what is still missing for general-purpose robots.模型与训练RoboticsMultimodal AI+3
1:15:59EN
Lex Fridman播客Steering Through Time: How Recurrent Networks and LSTMs Learn from Sequences主持 Lex FridmanLex Fridman's MIT 6.S094 lecture walks from backpropagation basics to LSTMs and the way they are used to predict steering in self-driving cars.模型与训练Deep Learning机器学习基础+2
1:03:59EN
Cognitive Revolution "How AI Changes Everything"播客Building a World Model of Life: Biohub's Alex Rives on Why Better Measurement Must Come Before Virtual Cells主持 Nathan LabenzBiohub's head of science explains why today's virtual cell models fall short, how a $1.8 billion data push aims to fix it, and what a five-year information-level model of the cell could unlock.模型与训练AI for scienceComputational Biology+3
18:46EN
Lex Fridman播客Deep Learning Plus One Idea: Ilya Sutskever on Building AGI主持 Lex FridmanIn a May 2020 conversation, Sutskever discusses self-play, simulation, bodies and consciousness, tests of intelligence, and how an AGI might be governed and aligned.模型与训练通用人工智能Reinforcement Learning+3
37:00EN
Lex Fridman播客Inside the YouTube Algorithm: Related Graphs, Satisfaction Surveys and the Viewers Who Are Part of the Code主持 Lex FridmanYouTube's head of search and discovery, Cristos Goodrow, explains to Lex Fridman how search and recommendations work, which signals matter, and how the team measures whether viewers are better off.模型与训练Recommendation systemsSearch & retrieval+3
1:31:52EN
Lex Fridman播客From Phonemes to CTC: How Deep Learning Rebuilt Speech Recognition主持 Lex FridmanBaidu's Adam Coates walks through the traditional speech pipeline, the CTC-based end-to-end engine that replaced much of it, and what it takes to scale and deploy it.模型与训练Deep LearningMultimodal AI+2
17:40EN
Lex Fridman播客From AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AI主持 Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.模型与训练Reinforcement LearningAI research+3
1:10:32EN → 简体中文
Lenny's Podcast播客 · 2 人对谈十亿美元、没有 VC、不到一百人:Surge AI 如何把数据质量做成一门艺术嘉宾 Edwin Chen · 主持 Lenny Rachitsky创始人 Edwin Chen 讲述这家自举的人类数据公司如何做到极高人均产值,为什么他完全不信排行榜,以及强化学习环境为何会成为下一阶段。模型与训练Company BuildingData quality & curation+3
1:10:19EN
Unsupervised Learning: With Jacob Effron播客The Robot That Folded the Laundry: Physical Intelligence’s Three Frontiers主持 Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.模型与训练RoboticsAI research+3
1:07:35EN
Lex Fridman播客Why AI Will Never Be Perfect: Lex Fridman's Case for Keeping Humans in the Loop主持 Lex FridmanIn MIT 6.S093's opening lecture, Lex Fridman lays out five research areas of human-centered AI, from machine teaching to arguing machines that flag their own uncertainty.模型与训练Human-AI Collaboration机器学习基础+3
10:16EN
Lex Fridman播客 · 2 人对谈Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think嘉宾 Yann Lecun · 主持 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.模型与训练机器学习基础Deep Learning+3
1:24:01EN → 简体中文
Lenny's Podcast播客从三明治称重到专家数据:Scale AI 新 CEO 谈什么真正让模型变聪明主持 Lenny RachitskyJason Droege 第一次以 Scale AI CEO 身份受访,讲清 Meta 投资之后公司仍独立,以及 Uber Eats 教会他怎样做生意。模型与训练Company BuildingData quality & curation+3
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