Résultats
21 articlesTrier
1:00:38EN
Lex Fridman· 6 déc. 2017PodcastThe 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.
58:46ENLex FridmanPodcastCaging 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.
1:15:59ENLex FridmanPodcastSteering 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.
1:07:22ENLex FridmanPodcastCars 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.
1:13:18ENLex FridmanPodcastHuman-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.
1:11:50ENLex FridmanPodcastData 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.
1:19:52ENLex FridmanPodcastFrom 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.
1:27:30ENLex FridmanPodcastFrom 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.
1:05:15ENLex FridmanPodcastTaming 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.
17:35ENLex FridmanPodcastHands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware ShopAnime : 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 FridmanPodcastThe 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.
37:18ENLex FridmanPodcastFrom 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.
53:13ENLex FridmanPodcastHow 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.
34:33ENLex FridmanPodcastTeaching 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.
17:32ENLex FridmanPodcastOver-Automating, Googling Doctors and Neural Nets: George Hotz Reviews Programming MemesAnime : Lex FridmanLex Fridman and George Hotz rate printed programming memes, and the jokes turn into candid talk about testing, hiring, social media and the power of neural networks.
11:29ENLex FridmanPodcastWhy Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has SeenAnime : Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.
1:31:29ENLex FridmanPodcastIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsAnime : 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.
1:02:24ENLex FridmanPodcastFrom Looping Forklifts to Self-Driving Cities: Sertac Karaman on Motion PlanningAnime : Lex FridmanAn MIT professor traces motion planning from the DARPA Urban Challenge to the future of transportation and the cities built around cars.
1:27:41ENLex FridmanPodcastDeep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes NextAnime : 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.
1:04:39ENLex FridmanPodcastFrom Udacity's Self-Driving Car Course to a Startup for Retirement Communities: Oliver Cameron on Building VoyageAnime : 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.
1:02:06ENLex FridmanPodcastDeep Learning for Self-Driving Cars: Why Edge Cases and Human Nature Are the Real ProblemAnime : Lex FridmanLex Fridman opens MIT's 6.S094 with a tour of what deep learning is, how it works, what it has achieved and where it still breaks, framed around autonomous vehicles.