絞り込み結果
282 件並び順
1:31:52EN
Lex FridmanポッドキャストFrom Phonemes to CTC: How Deep Learning Rebuilt Speech Recognitionホスト Lex FridmanBaidu's Adam Coates walks through the traditional speech pipeline, the CTC-based end-to-end engine that replaced much of it, and what it takes to scale and deploy it.
17:40ENLex FridmanポッドキャストFrom AlphaGo Zero to MuZero: How Self-Play Strips Knowledge Out of AIホスト Lex FridmanDeepMind's David Silver explains why removing human knowledge made AlphaZero stronger and more general, and how MuZero extended the idea to worlds with unknown rules.
1:10:32EN
Lenny's Podcastポッドキャスト · 2 人A Billion Dollars, No VC, Under 100 People: Surge AI's Edwin Chen on Data Quality and Where AI Is Headingゲスト Edwin Chen · ホスト 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.
1:10:19EN
Unsupervised Learning: With Jacob EffronポッドキャストThe Robot That Folded the Laundry: Physical Intelligence’s Three Frontiersホスト Jacob EffronKarol Hausman and Danny Driess explain how robot foundation models moved from coded primitives to web-scale pretraining, and why performance is now the hard gate.
1:07:35ENLex FridmanポッドキャストWhy AI Will Never Be Perfect: Lex Fridman's Case for Keeping Humans in the Loopホスト Lex FridmanIn MIT 6.S093's opening lecture, Lex Fridman lays out five research areas of human-centered AI, from machine teaching to arguing machines that flag their own uncertainty.
10:16ENLex Fridmanポッドキャスト · 2 人Reasoning Without Logic: Yann LeCun on Teaching Neural Networks to Thinkゲスト Yann Lecun · ホスト Lex FridmanYann LeCun explains why he believes neural networks can reason, and what memory, recurrence and continuous representations would need to look like.
1:24:01ENLenny's PodcastポッドキャストFrom Sandwich Math to Expert Data: Scale AI's CEO on What Actually Makes Models Smarterホスト Lenny RachitskyJason Droege explains what really happened with Meta's investment in Scale AI, how data labeling turned into expert work, and what Uber Eats taught him about building businesses.
16:41ENLex FridmanポッドキャストAlphaFold 2 and the Protein-Folding Breakthrough: Why Lex Fridman Calls It a Landmark for AI and Biologyホスト Lex FridmanA quick explainer on DeepMind's CASP14 result, how protein folding works, how AlphaFold 1 and 2 likely differ, and what the advance could unlock.
23:54EN
No Priors: AI, Machine Learning, Tech, & Startupsポッドキャスト · 2 人Beyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AIホスト 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.
1:19:52ENLex FridmanポッドキャストFrom Pixels to Steering Wheels: Convolutional Networks and End-to-End Drivingホスト Lex FridmanLex Fridman's MIT 6.S094 lecture explains how convolutional neural networks work, where deep learning helps a self-driving car, and how to train a network to steer from video.
57:21EN
Cognitive Revolution "How AI Changes Everything"ポッドキャストGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build Nextホスト Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
1:27:30ENLex FridmanポッドキャストFrom NAND Gates to Self-Driving Traffic: Deep Reinforcement Learning in One Lectureホスト Lex FridmanLex Fridman's second MIT 6.S094 lecture walks from the humble perceptron to deep Q-learning and the browser-based DeepTraffic competition.
1:05:15ENLex FridmanポッドキャストTaming the Long Tail: How Waymo Builds a Self-Driving Factoryホスト Lex FridmanWaymo principal scientist Drago Anguelov explains how machine learning infrastructure, hybrid design and smart simulated agents tackle the rare events of autonomous driving.
1:27:15ENLex FridmanポッドキャストPolicy Gradients vs. Q-Learning: John Schulman's Field Guide to Deep Reinforcement Learningホスト Lex FridmanOpenAI's John Schulman walks through the core methods of deep RL, from the score function estimator to TRPO and DQN, and says when each one is worth using.
1:19:21ENLex FridmanポッドキャストVapnik's Case for Learning by Predicates, Not Just by More Dataホスト Lex FridmanIn an MIT lecture, Vladimir Vapnik argues that complete statistical learning needs two mechanisms, data and invariants, and that choosing smart predicates is where intelligence lives.
1:03:25ENLex FridmanポッドキャストTheano in an Hour: Symbolic Graphs, Automatic Gradients and a Compiler That Rewrites Your Mathホスト Lex FridmanPascal Lamblin of MILA walks through how Theano builds, differentiates, optimizes and runs computation graphs, then trains logistic regression, a convnet and an LSTM.
1:08:06ENLex Fridmanポッドキャスト · 2 人Deep Learning in One Lecture: From Perceptrons to AutoML and the Limits of Learningゲスト Deep Learning Basics · ホスト 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.
57:25ENUnsupervised Learning: With Jacob EffronポッドキャストFrom RAG to Reasoning: Why the Future of AI Is a System, Not a Modelホスト Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.
13:58ENLex FridmanポッドキャストDeep Reinforcement Learning, Explained by the Researcher Behind AlphaGoホスト Lex FridmanDavid Silver of DeepMind walks through what reinforcement learning is, how its building blocks fit together, and why deep neural networks keep surprising even the experts.
57:55ENLex FridmanポッドキャストFrom Q-Tables to AlphaGo Zero: A Self-Driving Car Lecture on Deep Reinforcement Learningホスト Lex FridmanLex Fridman's MIT 6.S094 lecture walks from the AI pipeline and Q-learning to deep Q-networks, AlphaGo Zero and the DeepTraffic competition.
1:13:22ENLex FridmanポッドキャストThe Second 90%: What It Really Takes to Put Deep Learning on a Driverless Carホスト Lex FridmanWaymo's Sacha Arnoud walks MIT students through Waymo's history, its perception stack, and the industrial-scale labeling, compute and testing behind it.
57:15ENLex FridmanポッドキャストInside Torch and Autograd: How Deep Learning Libraries Compute Gradientsホスト Lex FridmanAlex Wiltschko of Twitter walks through Lua Torch, then explains automatic differentiation and what separates modern deep learning frameworks.
1:12:12ENLenny's PodcastポッドキャストModels Are Grown, Not Built: What Anthropic's Interpretability Research Sees Inside Claudeホスト Lenny RachitskyAnthropic researcher Emmanuel Ameisen explains how studying a language model's intermediate computations reveals concepts, plans and surprising quirks, and why that matters for alignment.
1:20:58ENLex FridmanポッドキャストFrom Bag of Words to Attention: Quoc Le Teaches Sequence-to-Sequence Learning Through Email Repliesホスト Lex FridmanA Deep Learning School talk that builds sequence-to-sequence models step by step around one running example, automatic email reply, and then surveys memory and operation-augmented networks.もっと見る282 件中 24 件を表示