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Lex Fridman· 31 jul 2021Pódcast · 2 vocesThe Fallacy of the Successful First StepInvitado: Ishan Misra · Presenta: Lex FridmanBerkeley's Jitendra Malik explains why computer vision still looks easy, why fully autonomous driving is not near, and what children know that today's networks do not.
1:56:17ENLex Fridman· 19 abr 2021Pódcast · 2 vocesIf You Reran Earth a Million Times, Would Anything Like Us Appear?Invitado: Risto Miikkulainen · Presenta: Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.
2:01:07ENLex Fridman· 12 dic 2020Pódcast · 2 vocesMichael Littman isn’t waiting for a runaway god. He’s watching us.Invitado: Michael Littman · Presenta: Lex FridmanThe Brown reinforcement-learning researcher tells Lex Fridman why accidental superintelligence feels like a 747 assembling itself — and why social media, rote language, and theory of mind worry him more.
2:10:06ENLex Fridman· 14 ago 2020Pódcast · 2 vocesYou Might Have to Understand the World to Understand the Letter AInvitado: Dileep George · Presenta: Lex FridmanDileep George on recursive cortical networks, why a five-year-old can read any new CAPTCHA, and what the Wright brothers actually learned from birds.
1:41:37ENLex Fridman· 21 jul 2020Pódcast · 2 vocesThe Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't SolvedInvitado: Jitendra Malik · Presenta: Lex FridmanBerkeley's Jitendra Malik tells Lex Fridman why computer vision keeps underestimating itself, why full self-driving still needs cognition, and why vision is the parent of language.
1:37:31ENLex 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.Cargar másMostrando 24 de 267