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슬라이드 5장8:02EN
Matthew Berman· 2023년 4월 12일Meta’s Segment Anything: Promptable Image Masks and the SA-1B DatasetMatthew Berman · Forward FutureIn April 2023, Matthew Berman reviews Meta’s Segment Anything project and demonstrates selecting image regions with clicks, boxes and automatic mask generation. The model segments pixels; it does not by itself name every object or guarantee accurate results on every image.Computer Vision비전과 영상Deep Learning+1
슬라이드 9장15:37EN
Matthew Berman· 2023년 3월 22일AI News in March 2023: Firefly, Gen-2, Bard and Job ExposureMatthew Berman · Forward FutureMatthew Berman reviews early generative media launches, a labor-exposure study and single-image view synthesis.Generative mediaFuture of WorkAI research+2
1:21:20EN
Cognitive Revolution "How AI Changes Everything"· 2023년 3월 9일팟캐스트Freeze the eyes and the brain. Train only the optic nerve.진행자 Nathan LabenzJunnan Li and Dongxu Li tell Nathan Labenz how BLIP cleaned noisy web captions, and how BLIP-2 connected a frozen vision model to a frozen language model in under ten days on one A100.멀티모달과 미디어Multimodal AI비전과 영상+3
48:52EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 2월 9일팟캐스트 · 2명Users Wanted a Better Brush. Runway Built One-Click Greenscreen진행자 Sarah Guo, Elad GilRunway CEO Cristobal Valenzuela on why a model is not a product, why filmmakers hacked a four-frame-per-second tool, and why 80 percent is enough when nobody dies.멀티모달과 미디어Generative media비전과 영상+3
2:36:21EN
Lex 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.멀티모달과 미디어Multimodal AI비전과 영상+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
2:10:06EN
Lex 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.모델과 학습Neuroscience & AIWorld models+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
1:37:31EN
Lex 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.모델과 학습RoboticsReinforcement Learning+3
2:12:36EN
Lex 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.보안과 안전AI security안전과 거버넌스+3
1:17:29EN
Lex 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.AI in healthcareAI for scienceData quality & curation+3
1:15:58EN
Lex 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.모델과 학습머신러닝 기초AI research+3
1:59:37EN
Lex 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.기업과 전략Autonomous DrivingRobotics+3
24:22EN
Lex 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.모델과 학습Autonomous DrivingAutonomous Systems+3
9:59EN
Lex 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.모델과 학습머신러닝 기초Deep Learning+3
58:46EN
Lex 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.모델과 학습Autonomous DrivingDeep Learning+3
1:23:18EN
Cognitive Revolution "How AI Changes Everything"팟캐스트From GPT-2 to GPT-3 Moments in Robotics: Six DeepMind Papers on Bridging Robots and the Internet진행자 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.모델과 학습RoboticsMultimodal AI+3
1:03:24EN
Unsupervised Learning: With Jacob Effron팟캐스트Why Sora Bet on People, Not Just Pixels진행자 Jacob EffronThe Sora team explains how a video model became a social creation network, what cameos revealed about human creativity, and why the next frontier is world simulation.멀티모달과 미디어Generative media비전과 영상+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
58:19EN
Unsupervised Learning: With Jacob Effron팟캐스트Runway's Chris Valenzuela on Why Taste Beats Tools in Generative Media진행자 Jacob EffronChris Valenzuela, CEO of Runway, explains why generative media is still early, how taste and iteration shape the work, and what has to change before AI media becomes a new art form.멀티모달과 미디어Generative media비전과 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
1:19:34EN
Lenny's Podcast팟캐스트Fei-Fei Li on ImageNet, World Models and Why Everyone Has a Role in AI진행자 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.모델과 학습World models비전과 영상+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
34:33EN
Lex 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.모델과 학습Autonomous Driving비전과 영상+3
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