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57:55EN
Lex FridmanPodcastFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement LearningAnime : Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the AI pipeline and Q-learning to deep Q-networks, AlphaGo Zero and the DeepTraffic competition.Modèles et entraînementReinforcement LearningDeep Learning+3
1:13:22EN
Lex FridmanPodcastThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless CarAnime : 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.Modèles et entraînementAutonomous DrivingRobotics+3
57:15EN
Lex FridmanPodcastInside Torch and Autograd: How Deep Learning Libraries Compute GradientsAnime : Lex FridmanAlex Wiltschko of Twitter walks through Lua Torch, then explains automatic differentiation and what separates modern deep learning frameworks.Modèles et entraînementFondamentaux du MLDeep Learning+1
1:20:58EN
Lex FridmanPodcastFrom Bag of Words to Attention: Quoc Le Teaches Sequence-to-Sequence Learning Through Email RepliesAnime : Lex FridmanA Deep Learning School talk that builds sequence-to-sequence models step by step around one running example, automatic email reply, and then surveys memory and operation-augmented networks.Modèles et entraînementDeep LearningFondamentaux du ML+2
1:19:48EN
Lex FridmanPodcastBigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep LearningAnime : Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.Modèles et entraînementFondamentaux du MLDeep Learning+3
1:02:06EN
Lex FridmanPodcastLearning TensorFlow Hands-On: From a Mystery Line to Handwritten DigitsAnime : Lex FridmanGoogle Brain's Sherry Moore walks a Deep Learning School audience through how TensorFlow works and two core labs, linear regression and MNIST digit recognition.Modèles et entraînementInfrastructure et déploiementOpen-source ecosystems+3
53:13EN
Lex FridmanPodcastHow Machines Learn to See: From Pixel Differences to Convolutions, ResNets and Scene SegmentationAnime : 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.Modèles et entraînementComputer VisionDeep Learning+3
34:33EN
Lex FridmanPodcastTeaching Cars to Watch the Driver: Deep Learning for Semi-Autonomous VehiclesAnime : 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.Modèles et entraînementAutonomous DrivingVision et vidéo+3
52:28EN
Lex FridmanPodcast · 2 voixRay Kurzweil on Hierarchies, the Neocortex and Merging with AIInvité : Ray Kurzweil · Anime : Lex FridmanIn an MIT AGI course lecture, Kurzweil connects the history of neural networks to his hierarchical theory of the neocortex, language understanding at Google, longevity, jobs and existential risk.Modèles et entraînementAGIAI History+3
1:00:15EN
Lex FridmanPodcast · 2 voixCircuit Search, Hindsight and Self-Play: Ilya Sutskever's Case for Where Learning Is GoingInvité : Ilya Sutskever · Anime : Lex FridmanIn an MIT AGI lecture, OpenAI's co-founder explains why deep learning works, then walks through meta-learning, hindsight experience replay, sim-to-real transfer, self-play and learning goals from human feedback.Modèles et entraînementFondamentaux du MLDeep Learning+3
1:31:29EN
Lex FridmanPodcastIs Driving More Like Chess or Conversation? Lex Fridman's Opening Lecture on Deep Learning for Self-Driving CarsAnime : 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.Modèles et entraînementDeep LearningAutonomous Driving+3
1:12:00EN
Lex FridmanPodcastWhy Deep Learning Works at All: Yoshua Bengio on Composition, Saddle Points and the Case for Unsupervised LearningAnime : Lex FridmanIn a 2016 Deep Learning School talk, Yoshua Bengio explains the assumptions that let neural nets beat the curse of dimensionality and lays out the open challenges ahead.Modèles et entraînementFondamentaux du MLDeep Learning+2
1:02:24EN
Lex FridmanPodcastFrom Looping Forklifts to Self-Driving Cities: Sertac Karaman on Motion PlanningAnime : Lex FridmanAn MIT professor traces motion planning from the DARPA Urban Challenge to the future of transportation and the cities built around cars.Autonomous DrivingRoboticsAI research+2
1:27:41EN
Lex FridmanPodcastDeep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes NextAnime : Lex FridmanAn MIT lecture surveys the biggest advances of 2017 to 2019 across language, reinforcement learning, deep learning theory and autonomous vehicles, and lists Fridman's hopes for the year ahead.Modèles et entraînementDeep LearningAI research+3
51:18EN
Lex FridmanPodcast · 2 voixEngineering Intelligence: Lex Fridman's Opening Lecture for MIT's AGI CourseInvité : MIT AGI · Anime : Lex FridmanLex Fridman lays out an engineering-first approach to artificial general intelligence, previews the course's projects and guest speakers, and frames deep learning's limits.Modèles et entraînementAGIAI research+3
1:02:06EN
Lex FridmanPodcastDeep Learning for Self-Driving Cars: Why Edge Cases and Human Nature Are the Real ProblemAnime : Lex FridmanLex Fridman opens MIT's 6.S094 with a tour of what deep learning is, how it works, what it has achieved and where it still breaks, framed around autonomous vehicles.Modèles et entraînementAutonomous DrivingDeep Learning+3