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슬라이드0:59EN
Matthew Berman· 2026년 8월 28일A Laser Device Aims to Target MosquitoesMatthew Berman · Forward FutureMatthew Berman describes a proposed laser-based mosquito defense and the capabilities claimed in a short promotional video.AI researchPublic HealthComputer Vision
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
슬라이드 3장1:47EN
Matthew Berman· 2026년 1월 10일Turning 2D Images Into 3D Objects With Meta SAM 3DMatthew Berman · Forward FutureMatthew Berman demonstrates object selection, 3D generation and visual effects in a video made in partnership with Meta.Generative mediaComputer VisionMultimodal AI
슬라이드 3장5:55EN
Matthew Berman· 2026년 1월 2일Turning Images into 3D Models with Meta SAM 3DMatthew Berman · Forward FutureMatthew Berman demonstrates object extraction, body reconstruction, and a 3D-printing workflow in Meta's SAM Playground.Computer VisionGenerative mediaOpen-source ecosystems
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
슬라이드 5장8:39EN
Matthew Berman· 2024년 8월 6일Figure 02: A Look at Figure AI’s Humanoid Robot and Its Long-Term AmbitionsMatthew Berman · Forward FutureMatthew Berman examines Figure’s 2024 announcement, from redesigned hands and onboard vision to the company’s ambitions for physical labor and homes.RoboticsComputer VisionMultimodal AI+2
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
슬라이드 4장14:51EN
Matthew Berman· 2024년 5월 13일OpenAI’s 2024 GPT-4o Launch: Voice, Vision and Desktop DemosMira Murati, Mark Chen, Barret Zoph · OpenAIMira Murati, Mark Chen and Barret Zoph introduce GPT-4o and demonstrate voice interaction, visual tutoring, code explanation and translation.OpenAI멀티모달과 미디어음성 AI+2
슬라이드 2장0:57EN
Matthew Berman· 2024년 4월 26일Grok Vision Preview: Reading a Diagram and Explaining a MemeMatthew Berman · Forward FutureMatthew Berman reviews two early examples of visual understanding, from a handwritten workflow to a workplace joke.Multimodal AIComputer Vision
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
2:45:10EN
Lex Fridman· 2022년 1월 22일팟캐스트 · 2명A Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.모델과 학습World modelsComputer Vision+3
2:30:30EN
Lex 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.모델과 학습Computer VisionMultimodal AI+3
1:41:37EN
Lex 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.모델과 학습비전과 영상Autonomous Driving+3
1:22:51EN
Lex Fridman· 2020년 5월 19일팟캐스트 · 2명Density, Not Demos: Sertac Karaman on Robots That Fly and Drive게스트 Sertac Karaman · 진행자 Lex FridmanThe MIT roboticist and Optimus Ride co-founder on why sharing space with people is harder than building the machine, and why flying at transportation scale is still the tougher problem.RoboticsAutonomous DrivingAutonomous Systems+3
56:47EN
Lex Fridman· 2019년 9월 8일팟캐스트 · 2명Why Vijay Kumar Refuses to Call Them Drones게스트 Vijay Kumar · 진행자 Lex FridmanThe Penn roboticist on swarm design, true autonomy, and why batteries — not algorithms — still limit the sky.RoboticsAutonomous SystemsMulti-agent systems+3
1:09:11EN
Lex Fridman· 2019년 6월 10일팟캐스트 · 2명Don't Ship Autopilot: Gavin Miller on AI That Leaves Creatives in Charge게스트 Gavin Miller · 진행자 Lex FridmanAdobe Research's head tells Lex Fridman why smart defaults, fixable errors, and intern-scale bets matter more than a fully automatic Photoshop.제품과 UXGenerative mediaHuman-AI Collaboration+3
32:45EN
Lex Fridman· 2019년 4월 12일팟캐스트 · 2명Elon Musk: Every Driver Input Is an Error Tesla Autopilot Must Eliminate게스트 Elon Musk · 진행자 Lex FridmanAfter MIT published a study of functional vigilance on Autopilot, Lex Fridman sat down with Musk to argue about cameras on drivers, fleet data, and whether humans still belong in the loop.보안과 안전Autonomous Driving사람 참여 검증(HITL)+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
54:33EN
Lex Fridman팟캐스트 · 2명Vision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving Race게스트 Self-Driving Cars · 진행자 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.Autonomous DrivingDeep 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
15:43EN
Lex Fridman팟캐스트 · 2명Inside RIDER: The Rugged Black Box Behind MIT's Large-Scale Driving Study게스트 MIT-AVT · 진행자 Lex FridmanA walkthrough of the data-collection device MIT-AVT uses to record drivers and vehicles in semi-autonomous cars month after month.Autonomous Driving인프라와 배포Multimodal AI+2
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