필터 결과
107개정렬
42:45EN
Lex 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.
24:22ENLex Fridman팟캐스트 · 2명Craftsmanship, First Principles and the Road to Self-Driving: Jim Keller on Working with Elon Musk게스트 Jim Keller · 진행자 Lex FridmanThe veteran chip architect explains why he thinks autonomous driving is a tractable engineering problem, how Tesla's cost constraints shaped its hardware, and what he took from Musk's way of thinking.
15:01ENLex Fridman팟캐스트 · 2명Deep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still Lacks게스트 Daniel Kahneman · 진행자 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.
56:20EN
No Priors: AI, Machine Learning, Tech, & Startups팟캐스트 · 2명Biohub's Bet: Building Open AI World Models of Biology From Proteins Up to Cells진행자 Sarah Guo, Elad GilMark Zuckerberg, Priscilla Chan and Alex Rives explain why Biohub pairs a frontier AI lab with frontier wet-lab biology, and why it releases tools like ESMFold2 as open source.
1:28:53ENLex Fridman팟캐스트 · 2명Machine Learning for Business Students: Powerful, Narrow, and Easier to Fool Than You Think게스트 MIT Sloan · 진행자 Lex FridmanLex Fridman's non-technical MIT Sloan lecture explains how machine learning works, why it is so capable at perception, and where it still breaks in the real world.
11:11ENLex Fridman팟캐스트 · 2명Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General게스트 Yann Lecun · 진행자 Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
1:17:38ENLex Fridman팟캐스트 · 2명Brains Are Body Regulators: Lisa Feldman Barrett on Why Emotions Are Constructed, Not Detected게스트 Lisa Feldman Barrett · 진행자 Lex FridmanIn a guest talk for MIT's AGI course, neuroscientist Lisa Feldman Barrett explains why faces don't display emotions, why brains exist to run bodies, and what that means for building human-like AI.
1:10:32EN
Lenny's Podcast팟캐스트 · 2명A Billion Dollars, No VC, Under 100 People: Surge AI's Edwin Chen on Data Quality and Where AI Is Heading게스트 Edwin Chen · 진행자 Lenny RachitskySurge AI's founder explains how a bootstrapped team built the leading human-data company, why he distrusts benchmarks, and how reinforcement learning environments are the next frontier.
10:16ENLex Fridman팟캐스트 · 2명Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Think게스트 Yann Lecun · 진행자 Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
23:54ENNo Priors: AI, Machine Learning, Tech, & Startups팟캐스트 · 2명Beyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AI진행자 Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.
1:08:06ENLex 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.
10:34ENLex Fridman팟캐스트 · 2명Why Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AI게스트 François Chollet · 진행자 Lex FridmanFrançois Chollet explains why neural networks only interpolate between points they have seen, and why the best AI systems pair them with symbolic rules.
52:28ENLex 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.
1:00:15ENLex Fridman팟캐스트 · 2명Circuit Search, Hindsight and Self-Play: Ilya Sutskever's Case for Where Learning Is Going게스트 Ilya Sutskever · 진행자 Lex FridmanIn an MIT AGI lecture, OpenAI's co-founder explains why deep learning works, then walks through meta-learning, hindsight experience replay, sim-to-real transfer, self-play and learning goals from human feedback.
1:35:09ENLex Fridman팟캐스트 · 2명Reverse-Engineering the Child: Josh Tenenbaum's Case for Human-Like AI게스트 MIT AGI · 진행자 Lex FridmanMIT cognitive scientist Josh Tenenbaum argues that real machine intelligence needs models of the world, built by studying how babies think and learn, not just better pattern recognition.
32:41ENLex 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.
26:45ENLex Fridman팟캐스트 · 2명Start Small, Build Habits, Pick Your Team: Andrew Ng's Practical Advice for Learning Deep Learning게스트 Andrew Ng · 진행자 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.
11:23ENLex Fridman팟캐스트 · 2명Science Is a Self-Improving System That Isn't Exploding: Chollet on the Limits of an Intelligence Explosion게스트 François Chollet · 진행자 Lex FridmanFrançois Chollet uses the history of science to argue that recursive self-improvement meets exponential friction and yields linear, not explosive, progress.
51:18ENLex Fridman팟캐스트 · 2명Engineering Intelligence: Lex Fridman's Opening Lecture for MIT's AGI Course게스트 MIT AGI · 진행자 Lex FridmanLex Fridman lays out an engineering-first approach to artificial general intelligence, previews the course's projects and guest speakers, and frames deep learning's limits.