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1:55:04EN
Lex FridmanPodcast · 2 speakersMining the Computational Universe: Stephen Wolfram on What AI Can and Can't Be Told to DoGuest Stephen Wolfram · Host Lex FridmanIn a talk for MIT's AGI course, Stephen Wolfram connects Wolfram Alpha, simple programs, computational irreducibility and the problem of telling machines what humans want.AGIAI HistoryAI Alignment+1
1:03:25EN
Lex FridmanPodcastTheano in an Hour: Symbolic Graphs, Automatic Gradients and a Compiler That Rewrites Your MathHost Lex FridmanPascal Lamblin of MILA walks through how Theano builds, differentiates, optimizes and runs computation graphs, then trains logistic regression, a convnet and an LSTM.Models & trainingDeep LearningML fundamentals+3
1:08:06EN
Lex FridmanPodcast · 2 speakersDeep Learning in One Lecture: From Perceptrons to AutoML and the Limits of LearningGuest Deep Learning Basics · Host Lex FridmanLex Fridman's opening lecture for MIT's 6.S094 course surveys why deep learning took off, how neural networks learn, and where the technique still falls short.Models & trainingDeep LearningML fundamentals+3
1:00:25EN
Lex FridmanPodcast · 2 speakersCan Machines Think? A Guided Tour of Turing's Test, Its Critics and Its SuccessorsGuest Turing Test · Host Lex FridmanLex Fridman walks through Alan Turing's 1950 paper, the objections to it, and the benchmarks that have tried to replace or extend the imitation game.AI HistoryBenchmarksPhilosophy+3
40:25EN
Lex FridmanPodcastA Language That Knows the World: Stephen Wolfram on Computable KnowledgeHost Lex FridmanIn this clip from the Lex Fridman Podcast, Stephen Wolfram explains what makes the Wolfram Language different from ordinary programming languages and how it grew into a computable knowledge base, from Wolfram Alpha to computational contracts.Programming LanguagesSoftware engineeringAI History
1:20:58EN
Lex FridmanPodcastFrom Bag of Words to Attention: Quoc Le Teaches Sequence-to-Sequence Learning Through Email RepliesHost 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.Models & trainingDeep LearningML fundamentals+2
52:28EN
Lex FridmanPodcast · 2 speakersRay Kurzweil on Hierarchies, the Neocortex and Merging with AIGuest Ray Kurzweil · Host 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.Models & trainingAGIAI History+3
32:41EN
Lex FridmanPodcast · 2 speakersHow IBM Watson Won Jeopardy: A Moonshot Built on Engineering, Not a BreakthroughGuest David Ferrucci · Host Lex FridmanDavid Ferrucci tells Lex Fridman how he talked IBM into the Jeopardy challenge and how his team built Watson's search, scoring and confidence machinery in about four years.Models & trainingAI HistorySearch & retrieval+1
11:59EN
Lex FridmanPodcast · 2 speakersFrom a Side Project to TensorFlow's Core: François Chollet on How Keras Came to BeGuest François Chollet · Host Lex FridmanThe creator of Keras recalls why he built it in 2015 around recurrent networks, how it moved onto TensorFlow, and what TensorFlow 2.0 means for its design.Open source & communityDeep LearningOpen-source ecosystems+3
1:27:41EN
Lex FridmanPodcastDeep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes NextHost 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.Models & trainingDeep LearningAI research+3