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1:50:08ENWaymo's Injury Rate Is Five Times Lower. It Still Loses to a Lyft.Moderation: Nathan LabenzHuman drivers average one fatal crash per 100 million miles — and that bar still defines the self-driving debate.
3:04:52ENDoctors Chose AI on Eight of Nine Dimensions: A GPT-4 Red-Teamer's Scouting ReportModeration: Nathan LabenzNathan Labenz tells 80,000 Hours what late-2023 systems can already do, which thresholds still matter, and why a polarized policy fight is a gift to heavy-handed regulation.
1:36:39ENOpenAI’s $5 Million Bet: A 60-Person Team Wants GPT-4V to Give Cars Common SenseModeration: Nathan LabenzGhost Autonomy cofounder John Hayes tells Cognitive Revolution why a multimodal model on the driving path could reset self-driving after two decades of DARPA-era stacks.
1:00:38ENThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle SafetyModeration: 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.
58:46ENCaging the Neural Network: How Aptiv Thinks About Safe Self-DrivingModeration: 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 SequencesModeration: 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 DataModeration: 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 FirstModeration: 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 MachineModeration: 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 WheelModeration: 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 RideModeration: 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 DrivingModeration: 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 LectureModeration: 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 FactoryModeration: Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
1:21:57ENBehind the Wheel: How Uber's Product Chief Dogfoods His Way to Better ProductsModeration: 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 CarModeration: 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 CompanyModeration: 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 MomentModeration: 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 SegmentationModeration: 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 VehiclesModeration: 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.
1:31:29ENIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsModeration: Lex FridmanThe first lecture of MIT 6.S094 introduces neural networks, reinforcement learning and computer vision through the question of how hard driving really is.
1:02:24ENFrom Looping Forklifts to Self-Driving Cities: Sertac Karaman on Motion PlanningModeration: Lex FridmanAn MIT professor traces motion planning from the DARPA Urban Challenge to the future of transportation and the cities built around cars.
1:27:41ENDeep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes NextModeration: Lex FridmanAn MIT lecture surveys the biggest advances of 2017 to 2019 across language, reinforcement learning, deep learning theory and autonomous vehicles, and lists Fridman's hopes for the year ahead.
1:04:39ENFrom Udacity's Self-Driving Car Course to a Startup for Retirement Communities: Oliver Cameron on Building VoyageModeration: Lex FridmanVoyage CEO Oliver Cameron tells the unconventional story of how a self-driving curriculum became a car, then a company that deploys in retirement communities, and what he learned along the way.
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