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9:59EN
Lex FridmanPódcastIs Language or Vision Harder? Ilya Sutskever on the Unity of Machine LearningPresenta: 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.
11:11ENLex FridmanPódcast · 2 vocesYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralInvitado: Yann Lecun · Presenta: 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.
10:16ENLex FridmanPódcast · 2 vocesReasoning Without Logic: Yann LeCun on Teaching Neural Networks to ThinkInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
13:58ENLex FridmanPódcastDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoPresenta: Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.
10:34ENLex FridmanPódcast · 2 vocesWhy Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AIInvitado: François Chollet · Presenta: Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.
10:39ENLex FridmanPódcastStatistics as Decision-Making: Michael I. Jordan on Bayesians, Frequentists and the Ideas Between ThemPresenta: Lex FridmanBerkeley's Michael I. Jordan explains where statistics came from, why it is really about decisions, and how empirical Bayes and false discovery rate bridge two rival philosophies.
11:59ENLex FridmanPódcast · 2 vocesFrom a Side Project to TensorFlow's Core: François Chollet on How Keras Came to BeInvitado: François Chollet · Presenta: 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.