筛选结果
61 篇排序
44:48EN → 简体中文Chris Urmson:无人驾驶之路,与能让你打个盹的那条路分道扬镳嘉宾 Chris Urmson · 主持 Lex FridmanLex Fridman 与 Aurora CEO Chris Urmson 聊了 DARPA 挑战赛、为什么激光雷达(lidar)是工具而非拐杖,以及 L2 辅助驾驶的经济账为什么长不成真正的自动驾驶。
32:45EN → 简体中文马斯克:驾驶员的每一次操作都是错误,特斯拉 Autopilot 必须消除嘉宾 Elon Musk · 主持 Lex FridmanMIT 发表了一项关于驾驶员使用 Autopilot 时功能性警觉的研究后,Lex Fridman 与马斯克坐下来,讨论车内摄像头、车队数据,以及人是否还应该留在驾驶回路里。
55:24EN → 简体中文Kyle Vogt 做出高速公路改装套件,还没卖出一台就砍掉了嘉宾 Kyle Vogt · 主持 Lex FridmanCruise 总裁兼首席技术官 Kyle Vogt 对 Lex Fridman 讲述:这位玩着 BattleBots 长大的堪萨斯少年,为什么放弃了一款能用的产品,转而与通用汽车合作,并在 2019 年把原型一步步推向量产。
1:26:21EN → 简体中文机器绝不该把自己的目标奉为圭臬嘉宾 Stuart Russell · 主持 Lex FridmanStuart Russell 与 Lex Fridman 谈元推理(metareasoning)、自动驾驶的可靠性,以及为什么对人类目标的不确定性是控制问题(control problem)的核心。
1:00:38ENThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle Safety主持 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 Race嘉宾 Self-Driving Cars · 主持 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-Driving主持 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 Sequences主持 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 Data主持 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.
1:24:24EN → 简体中文真正会改写农场、矿场和公路的,是装进重型机器里的智能主持 Lenny RachitskyApplied Intuition 联合创始人 Qasar Younis 认为,未来五到十年 AI 最大的冲击会落在车辆和工业机械上,并讲了这家安静做到 150 亿美元估值的公司如何定价值观、读书、做管理。
1:13:18ENHuman-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and Machine主持 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 Wheel主持 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.
42:16EN → 简体中文无人驾驶行程背后的产品纪律:Waymo 怎样把信任做成可设计的行为主持 Lenny RachitskyWaymo 产品管理高级总监 Shweta Shrivastava 解释自动驾驶产品如何赢得乘客信任、衡量安全,并撑住长期投入。
1:19:52ENFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End Driving主持 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 Lecture主持 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 Factory主持 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 Brain主持 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 Learning嘉宾 Deep Learning Basics · 主持 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.
1:21:57EN → 简体中文Uber 产品负责人自己开车送餐:亲测、快发,以及数据说不时仍要出手主持 Lenny RachitskyUber 首席产品官 Sachin Kansal 讲极端亲测、压缩交付周期、人车混跑的自动驾驶,以及几次跟数据对着干的下注。
1:13:22ENThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless Car主持 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 Company主持 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 Moment主持 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 Segmentation主持 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 Vehicles主持 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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