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19 篇
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1:29:02EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月1日播客From 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Explore主持 Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.企业与战略微调Agent orchestration+3
1:50:08EN → 简体中文
Cognitive Revolution "How AI Changes Everything"· 2024年8月7日播客Waymo 的受伤率低了五倍,却仍输给一辆 Lyft主持 Nathan Labenz人类司机平均每 1 亿英里才发生一起致命事故,这道门槛至今仍是自动驾驶争论的标尺。智能体Autonomous Driving安全与治理+3
1:16:11EN
Cognitive Revolution "How AI Changes Everything"· 2024年7月11日播客Scooping Food Into Boxes Is 70 Percent of Plant Labor主持 Nathan LabenzChef Robotics CEO Rajat Bhageria on 20 million plated meals, a foundation model for food, and why the kitchen may leave the house.RoboticsData quality & curationLocal inference+3
1:20:44EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月30日播客Seeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Days主持 Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.模型与训练AI researchTransformers & attention+3
1:40:07EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月4日播客Thirty thousand voltage updates a second: inside Skydio’s autonomy stack主持 Nathan LabenzHayk Martiros walks Nathan Labenz through a two-pound drone that sees in every direction, runs more than ten neural nets on board, and will not be weaponized.智能体RoboticsAutonomous Systems+3
2:45:10EN → 简体中文
Lex Fridman· 2022年1月22日播客 · 2 人对谈青少年二十小时学会开车,汽车却还学不会嘉宾 Yann Lecun · 主持 Lex FridmanYann LeCun 在 Lex Fridman 的播客里讲明白:自监督世界模型(self-supervised world models)为什么是智能缺失的“暗物质”,以及机器为什么还没到家猫的水平。模型与训练World modelsComputer Vision+3
2:30:30EN → 简体中文
Lex Fridman· 2021年7月31日播客 · 2 人对谈成功第一步的谬误嘉宾 Ishan Misra · 主持 Lex Fridman伯克利的 Jitendra Malik 解释了计算机视觉为何仍然看起来很简单、全自动驾驶为何还遥遥无期,以及孩子知道而今天的网络不知道的是什么。模型与训练Computer VisionMultimodal AI+3
1:41:37EN
Lex Fridman· 2020年7月21日播客 · 2 人对谈The Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't Solved嘉宾 Jitendra Malik · 主持 Lex FridmanBerkeley's Jitendra Malik tells Lex Fridman why computer vision keeps underestimating itself, why full self-driving still needs cognition, and why vision is the parent of language.模型与训练视觉与视频Autonomous Driving+3
1:22:51EN
Lex Fridman· 2020年5月19日播客 · 2 人对谈Density, Not Demos: Sertac Karaman on Robots That Fly and Drive嘉宾 Sertac Karaman · 主持 Lex FridmanThe MIT roboticist and Optimus Ride co-founder on why sharing space with people is harder than building the machine, and why flying at transportation scale is still the tougher problem.RoboticsAutonomous DrivingAutonomous Systems+3
56:47EN
Lex Fridman· 2019年9月8日播客 · 2 人对谈Why Vijay Kumar Refuses to Call Them Drones嘉宾 Vijay Kumar · 主持 Lex FridmanThe Penn roboticist on swarm design, true autonomy, and why batteries — not algorithms — still limit the sky.RoboticsAutonomous SystemsMulti-agent systems+3
1:09:11EN
Lex Fridman· 2019年6月10日播客 · 2 人对谈Don't Ship Autopilot: Gavin Miller on AI That Leaves Creatives in Charge嘉宾 Gavin Miller · 主持 Lex FridmanAdobe Research's head tells Lex Fridman why smart defaults, fixable errors, and intern-scale bets matter more than a fully automatic Photoshop.产品与体验Generative mediaHuman-AI Collaboration+3
32:45EN
Lex Fridman· 2019年4月12日播客 · 2 人对谈Elon Musk: Every Driver Input Is an Error Tesla Autopilot Must Eliminate嘉宾 Elon Musk · 主持 Lex FridmanAfter MIT published a study of functional vigilance on Autopilot, Lex Fridman sat down with Musk to argue about cameras on drivers, fleet data, and whether humans still belong in the loop.安全Autonomous Driving人工介入验证+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
54:33EN
Lex 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.Autonomous DrivingDeep LearningComputer Vision+3
1:11:50EN
Lex Fridman播客Data Is Everything: Teaching Self-Driving Cars to Understand the Human Behind the Wheel主持 Lex FridmanIn an MIT lecture, Lex Fridman shows how deep learning can sense pedestrians, driver posture, gaze, emotion and cognitive load, and why that matters for human-centered autonomy.多模态与媒体Deep Learning视觉与视频+3
1:19:52EN
Lex 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.模型与训练Autonomous DrivingDeep Learning+3
1:13:22EN
Lex 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.模型与训练Autonomous DrivingRobotics+3
15:43EN
Lex Fridman播客 · 2 人对谈Inside RIDER: The Rugged Black Box Behind MIT's Large-Scale Driving Study嘉宾 MIT-AVT · 主持 Lex FridmanA walkthrough of the data-collection device MIT-AVT uses to record drivers and vehicles in semi-autonomous cars month after month.Autonomous Driving基础设施与部署Multimodal AI+2
53:13EN
Lex Fridman播客How Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene Segmentation主持 Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the basics of image classification through landmark network architectures to pixel-level segmentation, optical flow and the SegFuse competition.模型与训练Computer VisionDeep Learning+3