筛选结果
344 篇排序
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.
11:11ENLex 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.
1:24:43ENLex 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.
1:17:38ENLex 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.
58:46ENLex 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.
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.
1:15:59ENLex 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.
1:03:59ENCognitive 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.
18:46ENLex 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.
37:00ENLex 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.
1:31:52ENLex 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.
17:40ENLex 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.
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。
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.
1:07:35ENLex 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.
10:16ENLex 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.
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。
16:41ENLex Fridman播客AlphaFold 2 and the Protein-Folding Breakthrough: Why Lex Fridman Calls It a Landmark for AI and Biology主持 Lex FridmanA quick explainer on DeepMind's CASP14 result, how protein folding works, how AlphaFold 1 and 2 likely differ, and what the advance could unlock.
23:54EN
No Priors: AI, Machine Learning, Tech, & Startups播客 · 2 人对谈Beyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AI主持 Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.
1:19:52ENLex Fridman播客From Pixels to Steering Wheels: Convolutional Networks and End-to-End Driving主持 Lex FridmanLex Fridman's MIT 6.S094 lecture explains how convolutional neural networks work, where deep learning helps a self-driving car, and how to train a network to steer from video.
57:21ENCognitive Revolution "How AI Changes Everything"播客Gemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build Next主持 Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
1:27:30ENLex Fridman播客From NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lecture主持 Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.
1:05:15ENLex Fridman播客Taming the Long Tail: How Waymo Builds a Self-Driving Factory主持 Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
1:27:15ENLex Fridman播客Policy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement Learning主持 Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.加载更多已显示 24 篇，共 344 篇