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1:08:06EN
Lex Fridman팟캐스트 · 2명Deep Learning in One Lecture: From Perceptrons to AutoML and the Limits of Learning게스트 Deep Learning Basics · 진행자 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.모델과 학습Deep Learning머신러닝 기초+3
1:00:25EN
Lex Fridman팟캐스트 · 2명Can Machines Think? A Guided Tour of Turing's Test, Its Critics and Its Successors게스트 Turing Test · 진행자 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 Fridman팟캐스트A Language That Knows the World: Stephen Wolfram on Computable Knowledge진행자 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 Fridman팟캐스트From Bag of Words to Attention: Quoc Le Teaches Sequence-to-Sequence Learning Through Email Replies진행자 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.모델과 학습Deep Learning머신러닝 기초+2
52:28EN
Lex Fridman팟캐스트 · 2명Ray Kurzweil on Hierarchies, the Neocortex and Merging with AI게스트 Ray Kurzweil · 진행자 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.모델과 학습AGI(범용 인공지능)AI History+3
32:41EN
Lex Fridman팟캐스트 · 2명How IBM Watson Won Jeopardy: A Moonshot Built on Engineering, Not a Breakthrough게스트 David Ferrucci · 진행자 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.모델과 학습AI HistorySearch & retrieval+1
11:59EN
Lex Fridman팟캐스트 · 2명From a Side Project to TensorFlow's Core: François Chollet on How Keras Came to Be게스트 François Chollet · 진행자 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.오픈소스와 커뮤니티Deep LearningOpen-source ecosystems+3
1:27:41EN
Lex Fridman팟캐스트Deep Learning in 2020: Lex Fridman's Tour of Transformers, Self-Play, Self-Driving and What Comes Next진행자 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.모델과 학습Deep LearningAI research+3