필터 결과
63개정렬
44:48ENChris Urmson: The Path to Driverless Cars Splits Away From the One That Lets You Nap게스트 Chris Urmson · 진행자 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 Eliminate게스트 Elon Musk · 진행자 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 One게스트 Kyle Vogt · 진행자 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 Gospel게스트 Stuart Russell · 진행자 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 Safety진행자 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.
24:22ENCraftsmanship, First Principles and the Road to Self-Driving: Jim Keller on Working with Elon Musk게스트 Jim Keller · 진행자 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.
54:33ENVision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving Race게스트 Self-Driving Cars · 진행자 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-Driving진행자 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 Sequences진행자 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 Data진행자 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 First진행자 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 Machine진행자 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 Wheel진행자 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 Ride진행자 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 Driving진행자 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 Lecture진행자 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 Factory진행자 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 Brain진행자 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 Learning게스트 Deep Learning Basics · 진행자 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 Products진행자 Lenny RachitskySachin Kansal on extreme dogfooding, shipping fast, Uber's hybrid autonomy strategy and making gut calls against the data.
17:35ENHands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware Shop진행자 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.
1:13:22ENThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless Car진행자 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.
15:43ENInside RIDER: The Rugged Black Box Behind MIT's Large-Scale Driving Study게스트 MIT-AVT · 진행자 Lex FridmanA walkthrough of the data-collection device MIT-AVT uses to record drivers and vehicles in semi-autonomous cars month after month.
37:18ENFrom Intelligent Copilots to Aurora: Sterling Anderson on Shared Control and Building a Self-Driving Company진행자 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.
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