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1:29:02EN
Cognitive Revolution "How AI Changes Everything"· 2026년 7월 1일팟캐스트From 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Explore진행자 Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.기업과 전략파인튜닝Agent orchestration+3
1:50:08EN
Cognitive Revolution "How AI Changes Everything"· 2024년 8월 7일팟캐스트Waymo's Injury Rate Is Five Times Lower. It Still Loses to a Lyft.진행자 Nathan LabenzHuman drivers average one fatal crash per 100 million miles — and that bar still defines the self-driving debate.에이전트Autonomous Driving안전과 거버넌스+3
1:16:11EN
Cognitive Revolution "How AI Changes Everything"· 2024년 7월 11일팟캐스트Scooping Food Into Boxes Is 70 Percent of Plant Labor진행자 Nathan LabenzChef Robotics CEO Rajat Bhageria on 20 million plated meals, a foundation model for food, and why the kitchen may leave the house.RoboticsData quality & curationLocal inference+3
1:20:44EN
Cognitive Revolution "How AI Changes Everything"· 2024년 3월 30일팟캐스트Seeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Days진행자 Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.모델과 학습AI researchTransformers & attention+3
1:40:07EN
Cognitive Revolution "How AI Changes Everything"· 2023년 7월 4일팟캐스트Thirty thousand voltage updates a second: inside Skydio’s autonomy stack진행자 Nathan LabenzHayk Martiros walks Nathan Labenz through a two-pound drone that sees in every direction, runs more than ten neural nets on board, and will not be weaponized.에이전트RoboticsAutonomous Systems+3
1:25:16EN
Lex Fridman팟캐스트From Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional Networks진행자 Lex FridmanA 2016 Deep Learning School talk covering how convnets work, how the ImageNet winners evolved, and how to apply them without being a hero.모델과 학습Deep LearningComputer Vision+3
1:11:50EN
Lex 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.멀티모달과 미디어Deep Learning비전과 영상+3
1:19:52EN
Lex 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.모델과 학습Autonomous DrivingDeep Learning+3
1:13:22EN
Lex 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.모델과 학습Autonomous DrivingRobotics+3
53:13EN
Lex 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.모델과 학습Computer VisionDeep Learning+3