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28 件
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1:50:08EN
Cognitive Revolution "How AI Changes Everything"· 2024年8月7日ポッドキャストWaymo's Injury Rate Is Five Times Lower. It Still Loses to a Lyft.ホスト Nathan LabenzHuman drivers average one fatal crash per 100 million miles — and that bar still defines the self-driving debate.エージェントAutonomous Driving安全性とガバナンス+3
3:04:52EN
Cognitive Revolution "How AI Changes Everything"· 2024年5月1日ポッドキャストDoctors Chose AI on Eight of Nine Dimensions: A GPT-4 Red-Teamer's Scouting Reportホスト Nathan LabenzNathan Labenz tells 80,000 Hours what late-2023 systems can already do, which thresholds still matter, and why a polarized policy fight is a gift to heavy-handed regulation.企業と戦略安全性とガバナンスAI research+3
1:36:39EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月9日ポッドキャストOpenAI’s $5 Million Bet: A 60-Person Team Wants GPT-4V to Give Cars Common Senseホスト Nathan LabenzGhost Autonomy cofounder John Hayes tells Cognitive Revolution why a multimodal model on the driving path could reset self-driving after two decades of DARPA-era stacks.エージェントAutonomous DrivingMultimodal AI+3
1:00:38EN
Lex Fridman· 2017年12月6日ポッドキャストThe Race Car and the Rulebook: Chris Gerdes on Automated Vehicle Safetyホスト 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.セキュリティと安全性Autonomous Driving安全性とガバナンス+3
58:46EN
Lex FridmanポッドキャストCaging the Neural Network: How Aptiv Thinks About Safe Self-Drivingホスト 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.モデルと学習Autonomous DrivingDeep Learning+3
1:15:59EN
Lex FridmanポッドキャストSteering Through Time: How Recurrent Networks and LSTMs Learn from Sequencesホスト 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.モデルと学習Deep Learning機械学習の基礎+2
1:07:22EN
Lex FridmanポッドキャストCars That Drive Empty: Emilio Frazzoli on Why Self-Driving Needs Rules, Not Just Dataホスト 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.Autonomous DrivingRoboticsAI startups & small teams+3
1:24:24EN
Lenny's PodcastポッドキャストIntelligence for Heavy Machines: Qasar Younis on Why Physical AI Will Change Farms, Mines and Roads Firstホスト 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.企業と戦略Autonomous SystemsRobotics+3
1:13:18EN
Lex FridmanポッドキャストHuman-Centered or Fully Autonomous? Lex Fridman's Case for Collaboration Between Driver and Machineホスト 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.Autonomous Driving安全性とガバナンスRobotics+3
1:11:50EN
Lex FridmanポッドキャストData Is Everything: Teaching Self-Driving Cars to Understand the Human Behind the Wheelホスト 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.マルチモーダルとメディアDeep Learning画像と動画+3
42:16EN
Lenny's PodcastポッドキャストThe Product Discipline Behind a Driverless Rideホスト Lenny RachitskyShweta Shrivastava of Waymo explains how autonomous-driving products earn trust, measure safety, and sustain long-term investment.プロダクトと UXProduct ManagementAutonomous Driving+3
1:19:52EN
Lex FridmanポッドキャストFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End Drivingホスト 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.モデルと学習Autonomous DrivingDeep Learning+3
1:27:30EN
Lex FridmanポッドキャストFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lectureホスト Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.モデルと学習Reinforcement LearningDeep Learning+2
1:05:15EN
Lex FridmanポッドキャストTaming the Long Tail: How Waymo Builds a Self-Driving Factoryホスト Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.モデルと学習Autonomous DrivingRobotics+3
1:21:57EN
Lenny's PodcastポッドキャストBehind the Wheel: How Uber's Product Chief Dogfoods His Way to Better Productsホスト Lenny RachitskySachin Kansal on extreme dogfooding, shipping fast, Uber's hybrid autonomy strategy and making gut calls against the data.プロダクトと UXProduct ManagementProduct Leadership+3
17:35EN
Lex FridmanポッドキャストHands Off the Wheel in San Diego: A Comma Two Demo Drive and a Tour of comma.ai's Hardware Shopホスト 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.プロダクトと UXAutonomous DrivingAI startups & small teams+3
1:13:22EN
Lex FridmanポッドキャストThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless Carホスト 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.モデルと学習Autonomous DrivingRobotics+3
37:18EN
Lex FridmanポッドキャストFrom Intelligent Copilots to Aurora: Sterling Anderson on Shared Control and Building a Self-Driving Companyホスト 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.Autonomous DrivingRoboticsHuman-AI Collaboration+2
1:13:40EN
Unsupervised Learning: With Jacob EffronポッドキャストThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Momentホスト 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.Autonomous DrivingRoboticsMultimodal AI+3
53:13EN
Lex FridmanポッドキャストHow Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene Segmentationホスト 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.モデルと学習Computer VisionDeep Learning+3
34:33EN
Lex FridmanポッドキャストTeaching Cars to Watch the Driver: Deep Learning for Semi-Autonomous Vehiclesホスト 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.モデルと学習Autonomous Driving画像と動画+3
17:32EN
Lex FridmanポッドキャストOver-Automating, Googling Doctors and Neural Nets: George Hotz Reviews Programming Memesホスト 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.Software engineering開発ワークフローとテストWorkflow automation+3
11:29EN
Lex FridmanポッドキャストWhy Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seenホスト Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.モデルと学習Autonomous DrivingRobotics+3
1:31:29EN
Lex FridmanポッドキャストIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving Carsホスト 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.モデルと学習Deep LearningAutonomous Driving+3
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