필터 결과
21개정렬
1:00:38EN
Lex Fridman· 2017년 12월 6일팟캐스트The 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.
58:46ENLex Fridman팟캐스트Caging 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.
1:15:59ENLex Fridman팟캐스트Steering 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.
1:07:22ENLex Fridman팟캐스트Cars 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.
1:13:18ENLex Fridman팟캐스트Human-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.
1:11:50ENLex Fridman팟캐스트Data 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.
1:19:52ENLex Fridman팟캐스트From 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.
1:27:30ENLex Fridman팟캐스트From 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.
1:05:15ENLex Fridman팟캐스트Taming 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.
17:35ENLex Fridman팟캐스트Hands 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.
1:13:22ENLex Fridman팟캐스트The 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.
37:18ENLex Fridman팟캐스트From 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.
53:13ENLex Fridman팟캐스트How Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene Segmentation진행자 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 Fridman팟캐스트Teaching Cars to Watch the Driver: Deep Learning for Semi-Autonomous Vehicles진행자 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 Fridman팟캐스트Over-Automating, Googling Doctors and Neural Nets: George Hotz Reviews Programming Memes진행자 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 Fridman팟캐스트Why Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seen진행자 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 Fridman팟캐스트Is Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving Cars진행자 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 Fridman팟캐스트From Looping Forklifts to Self-Driving Cities: Sertac Karaman on Motion Planning진행자 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 Fridman팟캐스트Deep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes Next진행자 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 Fridman팟캐스트From Udacity's Self-Driving Car Course to a Startup for Retirement Communities: Oliver Cameron on Building Voyage진행자 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 Fridman팟캐스트Deep Learning for Self-Driving Cars: Why Edge Cases and Human Nature Are the Real Problem진행자 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.