筛选结果
132 篇排序
42:45EN → 简体中文
Lex Fridman· 2018年12月16日播客 · 2 人对谈单腿机器人只凭“这个更好”学会了后空翻嘉宾 Pieter Abbeel · 主持 Lex FridmanPieter Abbeel 对 Lex Fridman 说明，为什么偏好比较、自我对弈、十分钟示范，以及杂乱的模拟器组合，是深度强化学习（RL）的切实路径。
1:00:38ENLex Fridman· 2017年12月6日播客The Race Car and the Rulebook: Chris Gerdes on Automated Vehicle Safety主持 Lex FridmanA Stanford engineer and former DOT innovation chief explains how autonomous racing, voluntary safety guidance, and data sharing could shape safer self-driving cars.
24:22ENLex 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.
54:33ENLex Fridman播客 · 2 人对谈Vision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving Race嘉宾 Self-Driving Cars · 主持 Lex FridmanThe opening lecture of MIT's 6.S094 course surveys 2018's milestones, the industry's optimistic predictions, and the beliefs about driving and humans that will decide who wins.
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.
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.
10:17ENLex Fridman播客Why Great Robots Fail as Businesses, and What iRobot Got Right主持 Lex FridmaniRobot co-founder Colin Angle explains why so many robotics companies collapse and how cost, vision and a clear user need shaped the Roomba.
1:07:22ENLex Fridman播客Cars That Drive Empty: Emilio Frazzoli on Why Self-Driving Needs Rules, Not Just Data主持 Lex FridmanThe nuTonomy CTO explains why full autonomy and shared fleets are where the value lies, and why the hardest open problem is deciding how vehicles should behave.
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.
1:24:24EN → 简体中文
Lenny's Podcast播客真正会改写农场、矿场和公路的，是装进重型机器里的智能主持 Lenny RachitskyApplied Intuition 联合创始人 Qasar Younis 认为，未来五到十年 AI 最大的冲击会落在车辆和工业机械上，并讲了这家安静做到 150 亿美元估值的公司如何定价值观、读书、做管理。
1:13:18ENLex Fridman播客Human-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and Machine主持 Lex FridmanLecture 2 of MIT's 2018 course on deep learning for self-driving cars covers the two paths to autonomy, how sensors compare, who is building what, and where deep learning can help.
1:18:48ENLex Fridman播客Data Movement, Not Math: How to Make Deep Learning Fit on Robots and Phones主持 Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.
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.
17:35ENLex Fridman播客Hands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware Shop主持 Lex FridmanAfter their podcast conversation, George Hotz takes Lex Fridman on an openpilot drive and then through the comma.ai offices, dashboards, assembly line and compute cluster.
1:13:22ENLex Fridman播客The Second 90%: What It Really Takes to Put Deep Learning on a Driverless Car主持 Lex FridmanWaymo's Sacha Arnoud walks MIT students through Waymo's history, its perception stack, and the industrial-scale labeling, compute and testing behind it.
18:46ENLex Fridman播客A Brooding Stuffed Hedgehog and Lex Fridman's Case for Owning Less主持 Lex FridmanIn an AMA, Lex Fridman uses his thrift-store hedgehog to talk about minimalism, anthropomorphism in robotics, and why shared experience binds people together.
37:18ENLex Fridman播客From Intelligent Copilots to Aurora: Sterling Anderson on Shared Control and Building a Self-Driving Company主持 Lex FridmanA guest lecture in MIT's 6.S094 course tracing Anderson's path from shared human-machine control research, through Tesla Autopilot, to co-founding Aurora.
1:39:10EN → 简体中文Lenny's Podcast播客键盘之后才是正戏：硬件老将眼里的物理 AI 浪潮主持 Lenny Rachitsky先后在 Apple、Meta、OpenAI 做硬件的 Caitlin Kalinowski 解释机器人热潮从何而来、量产真正卡在哪、以及怎样把硬件做出货。
1:13:40ENUnsupervised 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.
1:19:34EN → 简体中文Lenny's Podcast播客李飞飞谈 ImageNet、世界模型，以及为什么每个人都该在 AI 里有位置主持 Lenny Rachitsky常被称为「AI 教母」的科学家，回溯大数据如何点燃深度学习，解释空间智能为何是下一站，并演示 World Labs 的第一款产品 Marble。
11:29ENLex Fridman播客Why Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seen主持 Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.
1:48:13ENCognitive Revolution "How AI Changes Everything"播客Robotics Hits Its GPT-3.5 Moment: Inside Gemini Robotics, From Embodied Reasoning to Origami主持 Nathan LabenzGoogle DeepMind researchers Keerthana Gopalakrishnan and Ted Xiao explain how Gemini Robotics works, what it can and cannot do, and where the field goes next.加载更多已显示 24 篇，共 132 篇