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317 件並び順
8:05ENA 2023 Guide to Running the Original GPT4All Model LocallyMatthew Berman · Forward FutureMatthew Berman demonstrates an early CPU-based GPT4All release, its terminal installation and the resources available for fine-tuning.
6:50ENRunning LLaMA and Alpaca Locally: A 2023 Dalai TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup on a MacBook Air and explains the settings that control generation.
7:55ENHow to Train a Custom Image Model in Leonardo.aiMatthew Berman · Forward FutureMatthew Berman walks through Leonardo.ai’s 2023 model galleries, training-set guidance, and custom model workflow, then shares results from several experiments.
1:03:29ZH多模态论文串讲:BLIP、CoCa 与 BEiT-3从图文数据清理到统一预训练,梳理三种视觉语言模型的结构、目标函数与相互联系。
1:07:10ZHInstructGPT 论文精读:从人工反馈到语言模型对齐从监督微调、奖励模型到 PPO,梳理 InstructGPT 的训练流程、实验结果与局限。
3:28:47ENKarpathy Calls Trained Neural Nets Complicated Alien Artifactsゲスト Andrej Karpathy · ホスト Lex FridmanOn Lex Fridman's podcast, Andrej Karpathy refuses the brain analogy, walks the Fermi paradox through Nick Lane's chemistry, and treats the Transformer as a general-purpose differentiable computer.
2:10:08ENGato Is Only the Beginningゲスト Oriol Vinyals · ホスト Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.
2:10:39ENDemis Hassabis: Solve Intelligence, Then Solve Everything Elseゲスト Demis Hassabis · ホスト Lex FridmanThe DeepMind CEO tells Lex Fridman why the Turing Test is the wrong exam, how AlphaFold rewrote biology, and why the quiet radio sky suggests we are probably alone.
2:45:10ENA Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.ゲスト Yann Lecun · ホスト Lex FridmanYann LeCun tells Lex Fridman why self-supervised world models are the missing dark matter of intelligence, and why machines are not even at the level of a house cat.
2:31:57ENJay McClelland on How Thought Emerges From Neural Networksゲスト Jay McClelland · ホスト Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.
2:51:33ENThe Self Is a GPT Prompt: Wojciech Zaremba on Consciousness, Codex, and Fermi's Silenceゲスト Wojciech Zaremba · ホスト Lex FridmanOpenAI co-founder Wojciech Zaremba tells Lex Fridman he thinks we might be alone in the universe — and that GPT-3, Codex, and a one-handed robot already hint at how intelligence is built.
2:18:29ENYour Cortex Is 150,000 Brains Voting on a Coffee Cupゲスト Jeff Hawkins · ホスト Lex FridmanJeff Hawkins tells Lex Fridman that intelligence is learning a model of the world, the neocortex is tens of thousands of independent maps that vote, and the fastest path to machine intelligence is reverse-engineering that sheet.
2:30:30ENThe Fallacy of the Successful First Stepゲスト Ishan Misra · ホスト 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.
1:56:17ENIf You Reran Earth a Million Times, Would Anything Like Us Appear?ゲスト Risto Miikkulainen · ホスト Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.
2:01:07ENMichael Littman isn’t waiting for a runaway god. He’s watching us.ゲスト Michael Littman · ホスト 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.
2:10:06ENYou Might Have to Understand the World to Understand the Letter Aゲスト Dileep George · ホスト 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.
1:41:37ENThe Fallacy of the Successful First Step: Jitendra Malik on Why Seeing Still Isn't Solvedゲスト Jitendra Malik · ホスト 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.
1:37:31ENThe Robot That Brought the Beer Was Being Teleoperatedゲスト Sergey Levine · ホスト 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.
2:00:32ENSlow Synapses Grow Fast Learners — Warmth Is the Harder Problemゲスト Matt Botvinick · ホスト 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.
3:00:18ENOnly a Simulation Can Be Consciousゲスト Joscha Bach · ホスト 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.
1:37:28ENWe Are Still Massively Underestimating Deep Learningゲスト Ilya Sutskever · ホスト 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.
1:48:01ENDavid Silver: AlphaGo Won by Taking Human Knowledge Outゲスト David Silver · ホスト 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.
1:12:48ENJohn Hopfield's Physics of Mind: Glitches Become Featuresゲスト John Hopfield · ホスト 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.
1:44:55ENIf You Need 60,000 Digits, You Have Not Found Intelligenceゲスト Vladimir Vapnik · ホスト 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.
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