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26:02EN
Lex Fridman· 9 feb 2020PódcastMoore’s Law Is Not Dead—It Is a Cascade of S-CurvesPresenta: Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.Infraestructura y despliegueSemiconductorsScaling Laws+3
15:01EN
Lex FridmanPódcast · 2 vocesDeep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still LacksInvitado: Daniel Kahneman · Presenta: 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.Modelos y entrenamientoDeep LearningAI research+3
17:40EN
Lex FridmanPódcastFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIPresenta: 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.Modelos y entrenamientoReinforcement LearningAI research+3
20:36EN
Lex FridmanPódcastWhy Simple Theories Win: Marcus Hutter on Occam's Razor, Compression and Kolmogorov ComplexityPresenta: Lex FridmanDeepMind researcher Marcus Hutter explains Solomonoff induction, why compression equals understanding, and how a simple universe can still look rich.Modelos y entrenamientoFundamentos de MLAI research+3
20:50EN
Lex FridmanPódcastGlitches as Features: What John Hopfield Says Artificial Neural Networks Are MissingPresenta: Lex FridmanIn a short conversation with Lex Fridman, physicist and neural-network pioneer John Hopfield compares evolved brains with today's artificial networks and explains why he expects AI to borrow from biology generation after generation.Modelos y entrenamientoNeuroscience & AIFundamentos de ML+3
26:45EN
Lex FridmanPódcast · 2 vocesStart Small, Build Habits, Pick Your Team: Andrew Ng's Practical Advice for Learning Deep LearningInvitado: Andrew Ng · Presenta: Lex FridmanIn a clip from the Lex Fridman Podcast, Andrew Ng explains how to begin in deep learning, how to study effectively, and how to choose a career path.Modelos y entrenamientoDeep LearningFundamentos de ML+3