필터 결과
307개정렬
2:00:32EN
Lex Fridman· 2020년 7월 3일팟캐스트 · 2명Slow Synapses Grow Fast Learners — Warmth Is the Harder Problem게스트 Matt Botvinick · 진행자 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· 2020년 6월 13일팟캐스트 · 2명Only a Simulation Can Be Conscious게스트 Joscha Bach · 진행자 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· 2020년 5월 8일팟캐스트 · 2명We Are Still Massively Underestimating Deep Learning게스트 Ilya Sutskever · 진행자 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· 2020년 4월 3일팟캐스트 · 2명David Silver: AlphaGo Won by Taking Human Knowledge Out게스트 David Silver · 진행자 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· 2020년 2월 29일팟캐스트 · 2명John Hopfield's Physics of Mind: Glitches Become Features게스트 John Hopfield · 진행자 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· 2020년 2월 14일팟캐스트 · 2명If You Need 60,000 Digits, You Have Not Found Intelligence게스트 Vladimir Vapnik · 진행자 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· 2019년 11월 25일팟캐스트 · 2명Gilbert Strang still teaches with thick chalk and four subspaces게스트 Gilbert Strang · 진행자 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· 2019년 10월 27일팟캐스트 · 2명The Machine Has a Steady Hand: Garry Kasparov on Deep Blue, AlphaZero, and Putin게스트 Garry Kasparov · 진행자 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· 2019년 10월 3일팟캐스트 · 2명Gary Marcus: Deep Learning Imitates Intelligence. It Does Not Understand.게스트 Gary Marcus · 진행자 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· 2019년 9월 30일팟캐스트 · 2명You Can't Have Both Kinds of Fairness, Says Peter Norvig게스트 Peter Norvig · 진행자 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· 2019년 9월 14일팟캐스트 · 2명Intelligence is not the height of a building: François Chollet on Keras, deep learning, and why AGI will not explode게스트 François Chollet · 진행자 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· 2019년 8월 31일팟캐스트 · 2명Human Intelligence Is a Ridiculously Narrow Sliver게스트 Yann Lecun · 진행자 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· 2019년 8월 27일팟캐스트 · 2명A Single GPU Is Enough: Jeremy Howard on Teaching Deep Learning게스트 Jeremy Howard · 진행자 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· 2019년 7월 1일팟캐스트 · 2명The Brain Does Not Classify Images. It Navigates Maps.게스트 Jeff Hawkins · 진행자 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· 2019년 4월 18일팟캐스트 · 2명A Bar in Montreal, Then a Night of Code: Ian Goodfellow on Why GANs Work게스트 Ian Goodfellow · 진행자 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· 2019년 1월 19일팟캐스트 · 2명Einstein Was the Worst of Five Ph.D. Students게스트 Tomaso Poggio · 진행자 Lex FridmanMIT neuroscientist Tomaso Poggio on why intelligence is science's deepest problem, and what brains still have to teach machines.
46:25ENLex Fridman· 2019년 1월 17일팟캐스트Deep Learning at the Edge of 2019: BERT, Autopilot, and the Ideas That Broke Through진행자 Lex FridmanA tour of the architectural, applied, and automation breakthroughs that defined deep learning in 2018 and set up 2019.
1:19:59ENLex Fridman· 2018년 12월 23일팟캐스트 · 2명Schmidhuber’s bet: true meta-learning rewrites the learner, not the last layer게스트 Juergen Schmidhuber · 진행자 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· 2018년 12월 16일팟캐스트 · 2명A one-legged robot learned a backflip from "this is better"게스트 Pieter Abbeel · 진행자 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· 2018년 11월 16일팟캐스트 · 2명The Hardest Part of Learning Was Left Out of the Textbooks게스트 Vladimir Vapnik · 진행자 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· 2018년 10월 20일팟캐스트 · 2명An Adult Can Change Last Year's Mind. A Network Still Cannot.게스트 Yoshua Bengio · 진행자 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· 2016년 9월 27일팟캐스트From Word Vectors to Memory Networks: The Building Blocks of Deep NLP진행자 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 Fridman팟캐스트Deep Learning From the Ground Up: Hugo Larochelle's One-Hour Tour of Neural Network Foundations진행자 Lex FridmanA fast, equation-level walk through feed-forward networks, backpropagation, practical training tricks, dropout and batch normalization, from the 2016 Deep Learning School.
1:56:35EN
Cognitive Revolution "How AI Changes Everything"팟캐스트From Autocomplete to Alien Optimizer: Riley Goodside on Three Eras of Prompting진행자 Nathan LabenzScale AI's first staff prompt engineer traces how language models went from pure text prediction to instruction following to RLHF, and what that means for building with them.더 보기307개 중 24개 표시