필터 결과
20개정렬
4:18:22EN
Lex Fridman· 2026년 5월 6일팟캐스트 · 2명Every Cycle Matters: The Volunteers Who Decode Almost All Internet Video게스트 FFmpeg · 진행자 Lex FridmanLex Fridman talks with Jean-Baptiste Kempf and Kieran Kunhya about FFmpeg, VLC, handwritten assembly, and the unpaid crew behind YouTube, Netflix, and a rover on Mars.
1:55:10ENLex Fridman· 2024년 3월 18일팟캐스트 · 2명Sam Altman Expects the Road to AGI to Be a Power Struggle게스트 Sam Altman · 진행자 Lex FridmanOn a Friday afternoon in November 2023, OpenAI's board fired its CEO. Four and a half days later he was back, still refusing super-voting control.
2:36:21ENLex Fridman· 2022년 9월 21일팟캐스트 · 2명A Smile Is Not Happiness: Rana el Kaliouby on Emotion AI and the Empathy Crisis게스트 Rana el Kaliouby · 진행자 Lex FridmanThe Affectiva founder and Smart Eye deputy CEO talks with Lex Fridman about teaching machines to read faces, sensing drivers inside the cabin, and why she is proudest of the people her company grew.
2:30:30ENLex Fridman· 2021년 7월 31일팟캐스트 · 2명The Fallacy of the Successful First Step게스트 Ishan Misra · 진행자 Lex FridmanBerkeley's Jitendra Malik explains why computer vision still looks easy, why fully autonomous driving is not near, and what children know that today's networks do not.
2:10:06ENLex Fridman· 2020년 8월 14일팟캐스트 · 2명You Might Have to Understand the World to Understand the Letter A게스트 Dileep George · 진행자 Lex FridmanDileep George on recursive cortical networks, why a five-year-old can read any new CAPTCHA, and what the Wright brothers actually learned from birds.
1:41:37ENLex Fridman· 2020년 7월 21일팟캐스트 · 2명The Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't Solved게스트 Jitendra Malik · 진행자 Lex FridmanBerkeley's Jitendra Malik tells Lex Fridman why computer vision keeps underestimating itself, why full self-driving still needs cognition, and why vision is the parent of language.
1:37:31ENLex Fridman· 2020년 7월 14일팟캐스트 · 2명The Robot That Brought the Beer Was Being Teleoperated게스트 Sergey Levine · 진행자 Lex FridmanSergey Levine tells Lex Fridman why hardware is almost closed, why common sense has to be lived, and why offline reinforcement learning is the missing on-ramp from logs to robots that keep getting better.
2:12:36ENLex Fridman· 2020년 5월 12일팟캐스트 · 2명Attacks Climb the Stack Until They Land on People게스트 Dawn Song · 진행자 Lex FridmanDawn Song tells Lex Fridman why the next security crisis is human, how a sticker can rewrite a stop sign, and why data still has no property right.
1:17:29ENLex Fridman· 2019년 9월 23일팟캐스트 · 2명The Algorithm Is Already Better. The Clinic Still Uses 1967.게스트 Regina Barzilay · 진행자 Lex FridmanMIT's Regina Barzilay on why deep learning already beats the breast-cancer 'density' score — and why data, liability, and incentives still will not move.
1:15:58ENLex Fridman· 2019년 8월 31일팟캐스트 · 2명Human Intelligence Is a Ridiculously Narrow Sliver게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun tells Lex Fridman why giant nets plus gradient descent broke the textbooks, why "AGI" is the wrong word, and why the next leap is a world model learned like a baby.
1:59:37ENLex Fridman· 2019년 8월 5일팟캐스트 · 2명Lane Centering Is the Only Self-Driving Feature That Already Helps게스트 George Hotz · 진행자 Lex Fridmancomma.ai founder George Hotz tells Lex Fridman why staying in the lane beats Level 5 promises, and why a robotaxi stack still has no network effect.
24:22ENLex Fridman팟캐스트 · 2명Craftsmanship, First Principles and the Road to Self-Driving: Jim Keller on Working with Elon Musk게스트 Jim Keller · 진행자 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.
9:59ENLex Fridman팟캐스트Is Language or Vision Harder? Ilya Sutskever on the Unity of Machine Learning진행자 Lex FridmanIn a short clip from his 2020 conversation with Lex Fridman, Ilya Sutskever explains why vision, language and reinforcement learning share the same few principles, and why asking which problem is harder is the wrong question.
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.
1:11:50ENLex 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.
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.
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.