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Lex Fridman· 14 jul 2020Pódcast · 2 vocesThe Robot That Brought the Beer Was Being TeleoperatedInvitado: Sergey Levine · Presenta: Lex FridmanSergey Levine tells Lex Fridman why hardware is almost closed, why common sense has to be lived, and why offline reinforcement learning is the missing on-ramp from logs to robots that keep getting better.
2:00:32ENLex Fridman· 3 jul 2020Pódcast · 2 vocesSlow Synapses Grow Fast Learners — Warmth Is the Harder ProblemInvitado: Matt Botvinick · Presenta: Lex FridmanDeepMind neuroscience director Matt Botvinick tells Lex Fridman how prefrontal cortex, meta-reinforcement learning, and dopamine research meet the human question of what a better life with AI would actually look like.
3:00:18ENLex Fridman· 13 jun 2020Pódcast · 2 vocesOnly a Simulation Can Be ConsciousInvitado: Joscha Bach · Presenta: Lex FridmanJoscha Bach tells Lex Fridman why a neuron cannot feel anything, why existence is the default, and why this dying world is still the best level of the game.
1:37:28ENLex Fridman· 8 may 2020Pódcast · 2 vocesWe Are Still Massively Underestimating Deep LearningInvitado: Ilya Sutskever · Presenta: Lex FridmanIlya Sutskever tells Lex Fridman why 2012 was about conviction, why bigger models can get worse before they get better, and what he would do with an AGI.
1:48:01ENLex Fridman· 3 abr 2020Pódcast · 2 vocesDavid Silver: AlphaGo Won by Taking Human Knowledge OutInvitado: David Silver · Presenta: Lex FridmanThe DeepMind researcher behind AlphaGo and AlphaZero tells Lex Fridman how an unclaimed million-dollar Go prize, a BBC Micro at age seven, and a honeymoon insight led to superhuman self-play.
1:12:48ENLex Fridman· 29 feb 2020Pódcast · 2 vocesJohn Hopfield's Physics of Mind: Glitches Become FeaturesInvitado: John Hopfield · Presenta: Lex FridmanThe Princeton physicist walks Lex Fridman from a wobbly London bridge to Hopfield networks, consciousness-as-story, and why his famous model still does not explain learning.
1:44:55ENLex Fridman· 14 feb 2020Pódcast · 2 vocesIf You Need 60,000 Digits, You Have Not Found IntelligenceInvitado: Vladimir Vapnik · Presenta: Lex FridmanVladimir Vapnik tells Lex Fridman that intelligence is the art of shrinking a sea of functions with a few good predicates — and that MNIST, solved with sixty examples per class, is the test.
49:53ENLex Fridman· 25 nov 2019Pódcast · 2 vocesGilbert Strang still teaches with thick chalk and four subspacesInvitado: Gilbert Strang · Presenta: Lex FridmanThe MIT linear-algebra legend talks with Lex Fridman about OpenCourseWare, singular values, neural nets as a million folds, and why calculus hogged the undergraduate timetable.
55:24ENLex Fridman· 27 oct 2019Pódcast · 2 vocesThe Machine Has a Steady Hand: Garry Kasparov on Deep Blue, AlphaZero, and PutinInvitado: Garry Kasparov · Presenta: Lex FridmanThe former world champion tells Lex Fridman why losing to IBM still hurt, why chess was never the peak of intellect, and why he lives in New York.
1:25:01ENLex Fridman· 3 oct 2019Pódcast · 2 vocesGary Marcus: Deep Learning Imitates Intelligence. It Does Not Understand.Invitado: Gary Marcus · Presenta: Lex FridmanOn Lex Fridman's podcast, the NYU emeritus and Rebooting AI co-author argues that perception and reasoning need different tools — and that trustworthy AI is impossible until machines can represent harm, bottles, and intent.
1:03:13ENLex Fridman· 30 sept 2019Pódcast · 2 vocesYou Can't Have Both Kinds of Fairness, Says Peter NorvigInvitado: Peter Norvig · Presenta: Lex FridmanThe co-author of Artificial Intelligence: A Modern Approach walks Lex Fridman through recidivism scores, utility functions, Lisp, MOOCs, and why human-level intelligence should not be the goal.
1:59:49ENLex Fridman· 14 sept 2019Pódcast · 2 vocesIntelligence is not the height of a building: François Chollet on Keras, deep learning, and why AGI will not explodeInvitado: François Chollet · Presenta: Lex FridmanThe Keras creator tells Lex Fridman that intelligence lives in a brain, a body, and a problem, that science already is a recursively self-improving superhuman system with linear output, and that the real near-term danger is the newsfeed.
1:15:58ENLex Fridman· 31 ago 2019Pódcast · 2 vocesHuman Intelligence Is a Ridiculously Narrow SliverInvitado: Yann Lecun · Presenta: Lex FridmanYann LeCun tells Lex Fridman why giant nets plus gradient descent broke the textbooks, why "AGI" is the wrong word, and why the next leap is a world model learned like a baby.
1:44:11ENLex Fridman· 27 ago 2019Pódcast · 2 vocesA Single GPU Is Enough: Jeremy Howard on Teaching Deep LearningInvitado: Jeremy Howard · Presenta: Lex FridmanThe fast.ai founder tells Lex Fridman why domain experts, not more papers or more TPUs, will decide whether deep learning actually helps people.
2:09:42ENLex Fridman· 1 jul 2019Pódcast · 2 vocesThe Brain Does Not Classify Images. It Navigates Maps.Invitado: Jeff Hawkins · Presenta: Lex FridmanJeff Hawkins tells Lex Fridman why the neocortex stores the world as thousands of voting reference frames, and why scaling today's networks will not get us there.
1:08:37ENLex Fridman· 18 abr 2019Pódcast · 2 vocesA Bar in Montreal, Then a Night of Code: Ian Goodfellow on Why GANs WorkInvitado: Ian Goodfellow · Presenta: Lex FridmanLex Fridman talks with Ian Goodfellow about the 2014 invention of generative adversarial networks, adversarial examples as a security problem, and what still has to be built before machines can hold a fact the way a person does.
1:20:21ENLex Fridman· 19 ene 2019Pódcast · 2 vocesEinstein Was the Worst of Five Ph.D. StudentsInvitado: Tomaso Poggio · Presenta: Lex FridmanMIT neuroscientist Tomaso Poggio on why intelligence is science's deepest problem, and what brains still have to teach machines.
46:25ENLex Fridman· 17 ene 2019PódcastDeep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke ThroughPresenta: 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 dic 2018Pódcast · 2 vocesSchmidhuber’s bet: true meta-learning rewrites the learner, not the last layerInvitado: Juergen Schmidhuber · Presenta: 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 dic 2018Pódcast · 2 vocesA one-legged robot learned a backflip from "this is better"Invitado: Pieter Abbeel · Presenta: 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.
54:03ENLex Fridman· 16 nov 2018Pódcast · 2 vocesThe Hardest Part of Learning Was Left Out of the TextbooksInvitado: Vladimir Vapnik · Presenta: 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 oct 2018Pódcast · 2 vocesAn Adult Can Change Last Year's Mind. A Network Still Cannot.Invitado: Yoshua Bengio · Presenta: 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 2016PódcastFrom Word Vectors to Memory Networks: The Building Blocks of Deep NLPPresenta: 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 FridmanPódcastDeep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network FoundationsPresenta: Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.Cargar másMostrando 24 de 257