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Lex Fridman· 3. Okt. 2019Podcast · 2 StimmenGary Marcus: Deep Learning Imitates Intelligence. It Does Not Understand.Gast: Gary Marcus · Moderation: 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.
1:17:29ENLex Fridman· 23. Sept. 2019Podcast · 2 StimmenThe Algorithm Is Already Better. The Clinic Still Uses 1967.Gast: Regina Barzilay · Moderation: Lex FridmanMIT's Regina Barzilay on why deep learning already beats the breast-cancer 'density' score — and why data, liability, and incentives still will not move.
1:59:49ENLex Fridman· 14. Sept. 2019Podcast · 2 StimmenIntelligence is not the height of a building: François Chollet on Keras, deep learning, and why AGI will not explodeGast: François Chollet · Moderation: 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.
1:44:11ENLex Fridman· 27. Aug. 2019Podcast · 2 StimmenA Single GPU Is Enough: Jeremy Howard on Teaching Deep LearningGast: Jeremy Howard · Moderation: 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.
1:10:58ENLex Fridman· 3. Juni 2019Podcast · 2 StimmenThe Hadoop Lesson That Made Google Give TensorFlow AwayGast: Rajat Monga · Moderation: Lex FridmanIn November 2015, Google put its core internal machine-learning system on GitHub. Rajat Monga explains why a company of that size would hand over the hard-to-copy part.
1:46:01ENLex Fridman· 29. Apr. 2019Podcast · 2 StimmenThe Night AlphaStar Beat TLO, the Team Went to a BarGast: Oriol Vinyals · Moderation: Lex FridmanOriol Vinyals on how DeepMind turned StarCraft II into a sequence problem, built a league of agents, and still refuses to call the game solved.
1:08:37ENLex Fridman· 18. Apr. 2019Podcast · 2 StimmenA Bar in Montreal, Then a Night of Code: Ian Goodfellow on Why GANs WorkGast: Ian Goodfellow · Moderation: 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. Jan. 2019Podcast · 2 StimmenEinstein Was the Worst of Five Ph.D. StudentsGast: Tomaso Poggio · Moderation: Lex FridmanMIT neuroscientist Tomaso Poggio on why intelligence is science's deepest problem, and what brains still have to teach machines.
1:19:59ENLex Fridman· 23. Dez. 2018Podcast · 2 StimmenSchmidhuber’s bet: true meta-learning rewrites the learner, not the last layerGast: Juergen Schmidhuber · Moderation: 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. Dez. 2018Podcast · 2 StimmenA one-legged robot learned a backflip from "this is better"Gast: Pieter Abbeel · Moderation: 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. 2018Podcast · 2 StimmenThe Hardest Part of Learning Was Left Out of the TextbooksGast: Vladimir Vapnik · Moderation: 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. Okt. 2018Podcast · 2 StimmenAn Adult Can Change Last Year's Mind. A Network Still Cannot.Gast: Yoshua Bengio · Moderation: 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.
15:01ENLex FridmanPodcast · 2 StimmenDeep Learning Is a System 1 Machine: Daniel Kahneman on What AI Still LacksGast: Daniel Kahneman · Moderation: 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.
54:33ENLex FridmanPodcast · 2 StimmenVision or Lidar, Human or Machine: Lex Fridman's 2019 Map of the Self-Driving RaceGast: Self-Driving Cars · Moderation: Lex FridmanThe opening lecture of MIT's 6.S094 course surveys 2018's milestones, the industry's optimistic predictions, and the beliefs about driving and humans that will decide who wins.
10:16ENLex FridmanPodcast · 2 StimmenReasoning Without Logic: Yann LeCun on Teaching Neural Networks to ThinkGast: Yann Lecun · Moderation: Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
17:21ENLex FridmanPodcast · 2 StimmenHow Alexa Learned to Hear From Across the Room: Rohit Prasad on Far-Field Speech and IntentGast: Rohit Prasad · Moderation: Lex FridmanAlexa's head scientist recalls the early days of the Echo, when far-field speech recognition seemed unsolvable and there were no customers to collect data from.
1:08:06ENLex FridmanPodcast · 2 StimmenDeep Learning in One Lecture: From Perceptrons to AutoML and the Limits of LearningGast: Deep Learning Basics · Moderation: 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.
24:08ENLex FridmanPodcast · 2 StimmenIntelligence Is Not Just Prediction: David Ferrucci on Explanation, Persuasion and Shared MeaningGast: David Ferrucci · Moderation: Lex FridmanThe lead of IBM's Watson team argues that predicting well is only half of intelligence, and that being understood by others is the other half.
10:34ENLex FridmanPodcast · 2 StimmenWhy Deep Learning Needs Rules: Chollet on Interpolation, Abstraction and Hybrid AIGast: François Chollet · Moderation: 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 FridmanPodcast · 2 StimmenRay Kurzweil on Hierarchies, the Neocortex and Merging with AIGast: Ray Kurzweil · Moderation: 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 FridmanPodcast · 2 StimmenCircuit Search, Hindsight and Self-Play: Ilya Sutskever's Case for Where Learning Is GoingGast: Ilya Sutskever · Moderation: 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.
11:59ENLex FridmanPodcast · 2 StimmenFrom a Side Project to TensorFlow's Core: François Chollet on How Keras Came to BeGast: François Chollet · Moderation: Lex FridmanThe creator of Keras recalls why he built it in 2015 around recurrent networks, how it moved onto TensorFlow, and what TensorFlow 2.0 means for its design.
26:45ENLex FridmanPodcast · 2 StimmenStart Small, Build Habits, Pick Your Team: Andrew Ng's Practical Advice for Learning Deep LearningGast: Andrew Ng · Moderation: 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.
51:18ENLex FridmanPodcast · 2 StimmenEngineering Intelligence: Lex Fridman's Opening Lecture for MIT's AGI CourseGast: MIT AGI · Moderation: 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.