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42:45EN
Lex Fridman· 16 dic 2018Pódcast · 2 vocesA one-legged robot learned a backflip from "this is better"Invitado: Pieter Abbeel · Presenta: Lex FridmanPieter Abbeel tells Lex Fridman why preference comparisons, self-play, ten-minute demos, and messy ensembles of simulators are the practical path through deep reinforcement learning.
1:00:38ENLex Fridman· 6 dic 2017PódcastThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle SafetyPresenta: 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.
24:22ENLex FridmanPódcast · 2 vocesCraftsmanship, First Principles and the Road to Self-Driving: Jim Keller on Working with Elon MuskInvitado: Jim Keller · Presenta: 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.
54:33ENLex FridmanPódcast · 2 vocesVision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving RaceInvitado: Self-Driving Cars · Presenta: 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.
11:11ENLex FridmanPódcast · 2 vocesYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralInvitado: Yann Lecun · Presenta: Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
58:46ENLex FridmanPódcastCaging the Neural Network: How Aptiv Thinks About Safe Self-DrivingPresenta: 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.
1:23:18EN
Cognitive Revolution "How AI Changes Everything"PódcastFrom GPT-2 to GPT-3 Moments in Robotics: Six DeepMind Papers on Bridging Robots and the InternetPresenta: Nathan LabenzKeerthana Gopalakrishnan and Ted Xiao walk through RT-2, RT-X, RT-Trajectory, AutoRT, Learning to Learn Faster and PIVOT, and say what is still missing for general-purpose robots.
10:17ENLex FridmanPódcastWhy Great Robots Fail as Businesses, and What iRobot Got RightPresenta: Lex FridmaniRobot co-founder Colin Angle explains why so many robotics companies collapse and how cost, vision and a clear user need shaped the Roomba.
1:07:22ENLex FridmanPódcastCars That Drive Empty: Emilio Frazzoli on Why Self-Driving Needs Rules, Not Just DataPresenta: 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.
1:10:19EN
Unsupervised Learning: With Jacob EffronPódcastThe Robot That Folded the Laundry: Physical Intelligence’s Three FrontiersPresenta: Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.
1:24:24EN
Lenny's PodcastPódcastIntelligence for Heavy Machines: Qasar Younis on Why Physical AI Will Change Farms, Mines and Roads FirstPresenta: 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.
1:13:18ENLex FridmanPódcastHuman-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and MachinePresenta: 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.
1:18:48ENLex FridmanPódcastData Movement, Not Math: How to Make Deep Learning Fit on Robots and PhonesPresenta: Lex FridmanMIT professor Vivienne Sze explains why moving data dominates the energy cost of neural networks and how co-designing hardware and algorithms can cut it by orders of magnitude.
1:05:15ENLex FridmanPódcastTaming the Long Tail: How Waymo Builds a Self-Driving FactoryPresenta: Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
1:27:15ENLex FridmanPódcastPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement LearningPresenta: Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.
17:35ENLex FridmanPódcastHands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware ShopPresenta: 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 FridmanPódcastThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless CarPresenta: 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.
18:46ENLex FridmanPódcastA Brooding Stuffed Hedgehog and Lex Fridman's Case for Owning LessPresenta: Lex FridmanIn an AMA, Lex Fridman uses his thrift-store hedgehog to talk about minimalism, anthropomorphism in robotics, and why shared experience binds people together.
37:18ENLex FridmanPódcastFrom Intelligent Copilots to Aurora: Sterling Anderson on Shared Control and Building a Self-Driving CompanyPresenta: 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.
1:39:10ENLenny's PodcastPódcastAfter the Keyboard: Why Physical AI Is the Next Frontier, According to a Veteran Hardware LeaderPresenta: Lenny RachitskyCaitlin Kalinowski, who has built products at Apple, Meta and OpenAI, explains why robotics is heating up, what actually gates it, and how to build hardware that ships.
1:13:40ENUnsupervised Learning: With Jacob EffronPódcastThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing MomentPresenta: 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.
1:19:34ENLenny's PodcastPódcastFei-Fei Li on ImageNet, World Models and Why Everyone Has a Role in AIPresenta: Lenny RachitskyThe scientist often called the godmother of AI traces how big data sparked deep learning, explains why spatial intelligence is the next frontier, and shows what World Labs' first product, Marble, can do.
11:29ENLex FridmanPódcastWhy Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has SeenPresenta: Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.
1:48:13ENCognitive Revolution "How AI Changes Everything"PódcastRobotics Hits Its GPT-3.5 Moment: Inside Gemini Robotics, From Embodied Reasoning to OrigamiPresenta: Nathan LabenzGoogle DeepMind researchers Keerthana Gopalakrishnan and Ted Xiao explain how Gemini Robotics works, what it can and cannot do, and where the field goes next.Cargar másMostrando 24 de 124