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Lex Fridman· 17. Jan. 2019PodcastDeep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke ThroughModeration: Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.
1:19:59ENLex Fridman· 23. Dez. 2018Podcast · 2 StimmenSchmidhuber’s bet: true meta-learning rewrites the learner, not the last layerGast: Juergen Schmidhuber · Moderation: Lex FridmanJürgen Schmidhuber tells Lex Fridman how Gödel machines, compression-as-science, Power Play, LSTMs, and world models all descend from a teenage plan to multiply one person’s curiosity into a better physicist than he could ever be.
42:45ENLex Fridman· 16. Dez. 2018Podcast · 2 StimmenA one-legged robot learned a backflip from "this is better"Gast: Pieter Abbeel · Moderation: Lex FridmanPieter Abbeel tells Lex Fridman why preference comparisons, self-play, ten-minute demos, and messy ensembles of simulators are the practical path through deep reinforcement learning.
1:26:21ENLex Fridman· 9. Dez. 2018Podcast · 2 StimmenThe Machine Should Never Treat Its Objective as GospelGast: Stuart Russell · Moderation: Lex FridmanStuart Russell talks with Lex Fridman about metareasoning, self-driving reliability, and why uncertainty about human goals is the core of the control problem.
54:03ENLex Fridman· 16. Nov. 2018Podcast · 2 StimmenThe Hardest Part of Learning Was Left Out of the TextbooksGast: Vladimir Vapnik · Moderation: Lex FridmanVladimir Vapnik tells Lex Fridman why intelligence is the work of inventing predicates that shrink the admissible set of functions, not of fitting a rule to a mountain of data.
42:18ENLex Fridman· 20. Okt. 2018Podcast · 2 StimmenAn Adult Can Change Last Year's Mind. A Network Still Cannot.Gast: Yoshua Bengio · Moderation: Lex FridmanYoshua Bengio tells Lex Fridman that the missing pieces of deep learning sit in credit assignment, training objectives, and a kind of compositionality borrowed from classical AI — not in ten thousand layers.
1:29:03ENLex Fridman· 27. Sept. 2016PodcastFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPModeration: Lex FridmanRichard Socher explains how word embeddings, recurrent models, GRUs, pointer mixtures, and dynamic memory networks turn language tasks into trainable end-to-end systems.
1:00:51ENLex FridmanPodcastDeep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network FoundationsModeration: Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.
1:07:29ENLex FridmanPodcastDeep Reinforcement Learning from First Principles: Rewards, Q-Learning, Policy Gradients and AlphaZeroModeration: Lex FridmanLex Fridman's MIT 6.S091 opening lecture walks from the basic RL framework through DQN, actor-critic methods and AlphaZero to the unsolved problem of moving from simulation to the real world.
9:59ENLex FridmanPodcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningModeration: 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.
15:01ENLex FridmanPodcast · 2 StimmenDeep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still LacksGast: Daniel Kahneman · Moderation: Lex FridmanThe Nobel-winning psychologist tells Lex Fridman how his fast-and-slow thinking framework maps onto deep learning, and why driving among pedestrians may require understanding people.
1:25:16ENLex FridmanPodcastFrom Hand-Built Features to ResNets: Andrej Karpathy's Crash Course in Convolutional NetworksModeration: 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.
1:28:53ENLex FridmanPodcast · 2 StimmenMachine Learning for Business Students: Powerful, Narrow, and Easier to Fool Than You ThinkGast: MIT Sloan · Moderation: Lex FridmanLex Fridman's non-technical MIT Sloan lecture explains how machine learning works, why it is so capable at perception, and where it still breaks in the real world.
11:11ENLex FridmanPodcast · 2 StimmenYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralGast: Yann Lecun · Moderation: Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
1:24:43ENLex FridmanPodcastFrom Sparse Coding to GANs: A Tour of Unsupervised Deep Learning in 2016Moderation: Lex FridmanRuslan Salakhutdinov walks through autoencoders, Boltzmann machines, variational autoencoders and adversarial networks at the Deep Learning School, with candid notes on what did and did not work.
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Lenny's PodcastPodcast · 2 StimmenStop Chasing AI News: Chip Huyen on What Actually Makes AI Products BetterGast: Chip Huyen · Moderation: Lenny RachitskyAuthor of AI Engineering walks through pre-training, post-training, RL, evals and RAG, then explains what separates companies that get value from AI from those that stall.
1:15:59ENLex FridmanPodcastSteering Through Time: How Recurrent Networks and LSTMs Learn from SequencesModeration: Lex FridmanLex Fridman's MIT 6.S094 lecture walks from backpropagation basics to LSTMs and the way they are used to predict steering in self-driving cars.
37:00ENLex FridmanPodcastInside the YouTube Algorithm: Related Graphs, Satisfaction Surveys and the Viewers Who Are Part of the CodeModeration: Lex FridmanYouTube's head of search and discovery, Cristos Goodrow, explains to Lex Fridman how search and recommendations work, which signals matter, and how the team measures whether viewers are better off.
1:31:52ENLex FridmanPodcastFrom Phonemes to CTC: How Deep Learning Rebuilt Speech RecognitionModeration: Lex FridmanBaidu's Adam Coates walks through the traditional speech pipeline, the CTC-based end-to-end engine that replaced much of it, and what it takes to scale and deploy it.
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No Priors: AI, Machine Learning, Tech, & StartupsPodcast · 2 StimmenIt's Six Months In: Misconceptions About AI, Regulation, Context Windows and IncumbentsModeration: Sarah Guo, Elad GilSarah Guo and Elad Gil answer listener questions on what the market gets wrong about generative AI, from the nuclear-regulation analogy to where startups can still beat incumbents.
17:40ENLex FridmanPodcastFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIModeration: Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.
1:07:35ENLex FridmanPodcastWhy AI Will Never Be Perfect: Lex Fridman's Case for Keeping Humans in the LoopModeration: Lex FridmanIn MIT 6.S093's opening lecture, Lex Fridman lays out five research areas of human-centered AI, from machine teaching to arguing machines that flag their own uncertainty.
10:16ENLex FridmanPodcast · 2 StimmenReasoning Without Logic: Yann LeCun on Teaching Neural Networks to ThinkGast: Yann Lecun · Moderation: Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
1:19:52ENLex FridmanPodcastFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End DrivingModeration: 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.Mehr laden24 von 101 angezeigt