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44:48ENChris Urmson: The Path to Driverless Cars Splits Away From the One That Lets You NapInvité : Chris Urmson · Anime : Lex FridmanLex Fridman talks with Aurora CEO Chris Urmson about the DARPA races, why lidar is a tool rather than a crutch, and why Level 2 economics will not grow into true autonomy.
32:45ENElon Musk: Every Driver Input Is an Error Tesla Autopilot Must EliminateInvité : Elon Musk · Anime : 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.
55:24ENKyle Vogt Built the Highway Kit, Then Scrapped It Before Selling a Single OneInvité : Kyle Vogt · Anime : Lex FridmanThe Cruise president and CTO tells Lex Fridman why a BattleBots kid from Kansas walked away from a working product, partnered with GM, and is spending 2019 grinding from prototype to production.
1:26:21ENThe Machine Should Never Treat Its Objective as GospelInvité : Stuart Russell · Anime : Lex FridmanStuart Russell talks with Lex Fridman about metareasoning, self-driving reliability, and why uncertainty about human goals is the core of the control problem.
1:00:38ENThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle SafetyAnime : 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.
54:33ENVision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving RaceInvité : Self-Driving Cars · Anime : 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.
58:46ENCaging the Neural Network: How Aptiv Thinks About Safe Self-DrivingAnime : 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.
1:15:59ENSteering Through Time: How Recurrent Networks and LSTMs Learn from SequencesAnime : 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.
1:07:22ENCars That Drive Empty: Emilio Frazzoli on Why Self-Driving Needs Rules, Not Just DataAnime : 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.
1:24:24ENIntelligence for Heavy Machines: Qasar Younis on Why Physical AI Will Change Farms, Mines and Roads FirstAnime : Lenny RachitskyThe Applied Intuition co-founder explains why the biggest near-term AI impact is in vehicles and industrial machines, and shares the values, reading habits and management philosophy behind a quiet $15 billion company.
1:13:18ENHuman-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and MachineAnime : 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.
1:11:50ENData Is Everything: Teaching Self-Driving Cars to Understand the Human Behind the WheelAnime : 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.
42:16ENThe Product Discipline Behind a Driverless RideAnime : Lenny RachitskyShweta Shrivastava of Waymo explains how autonomous-driving products earn trust, measure safety, and sustain long-term investment.
1:19:52ENFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End DrivingAnime : 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.
1:27:30ENFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One LectureAnime : Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.
1:05:15ENTaming the Long Tail: How Waymo Builds a Self-Driving FactoryAnime : Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
31:46ENWhy Rivian Threw Out Its First Self-Driving Stack and Built Its Own BrainAnime : Sarah Guo, Elad GilRivian founder RJ Scaringe explains the neural-net reset, in-house chips, software-defined architecture and the mass-market R2 bet.
1:08:06ENDeep Learning in One Lecture: From Perceptrons to AutoML and the Limits of LearningInvité : Deep Learning Basics · Anime : Lex FridmanLex Fridman's opening lecture for MIT's 6.S094 course surveys why deep learning took off, how neural networks learn, and where the technique still falls short.
1:21:57ENBehind the Wheel: How Uber's Product Chief Dogfoods His Way to Better ProductsAnime : Lenny RachitskySachin Kansal on extreme dogfooding, shipping fast, Uber's hybrid autonomy strategy and making gut calls against the data.
1:13:22ENThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless CarAnime : 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.
37:18ENFrom Intelligent Copilots to Aurora: Sterling Anderson on Shared Control and Building a Self-Driving CompanyAnime : 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.
1:13:40ENThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing MomentAnime : 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.
53:13ENHow Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene SegmentationAnime : 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.
34:33ENTeaching Cars to Watch the Driver: Deep Learning for Semi-Autonomous VehiclesAnime : Lex FridmanLex Fridman's MIT 6.S094 lecture on using driver-facing cameras and neural networks to understand body pose, gaze, emotion and cognitive load.
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