최근 업데이트된 채널

선택하면 해당 채널만 표시모든 채널 보기 →

필터 결과

248개
정렬
35:24EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 8월 24일팟캐스트 · 2명The Author of Attention Is All You Need Now Compiles mRNA Like Bytecode진행자 Sarah Guo, Elad GilJakob Uszkoreit on why Transformers won, why models spend compute on the wrong things, and why drug discovery has to become generation rather than screening.모델과 학습AI for scienceTransformers & attention+2
2:13:07EN
Cognitive Revolution "How AI Changes Everything"· 2023년 7월 27일팟캐스트Half an Hour to a Circuit in GPT-2 Small — and a Quadratic Wall Before GPT-3진행자 Nathan LabenzArthur Conmy walks Nathan Labenz through ACDC, the algorithm that automates the most tedious step of mechanistic interpretability: finding which transformer components actually do a task.모델과 학습Model InterpretabilityAI research+3
슬라이드 3장12:20EN
MBMatthew Berman· 2023년 7월 10일Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.Open-weight models평가(Evals)모델과 학습+1
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 2023년 7월 6일팟캐스트The AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understand진행자 Nathan LabenzNathan Labenz spends a solo episode walking through what general-purpose models can do, how they are trained, how capabilities unlock, and whether they understand anything at all.모델과 학습머신러닝 기초Scaling Laws+3
1:32:22EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 29일팟캐스트A Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer Away진행자 Nathan LabenzLili Yu of Meta AI explains a multiscale transformer that predicts million-byte sequences, skips tokenization, and aims to model any file as raw bytes.모델과 학습Multimodal AITransformers & attention+3
1:52:46EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 27일팟캐스트Charge Neural Nets by Connection Length, and the Black Box Splits Into Modules You Can See진행자 Nathan LabenzMIT physicist Ziming Liu walks Nathan Labenz through BIMT, a brain-inspired training trick that sparsifies networks until you can read them by looking.모델과 학습Model Interpretability머신러닝 기초+3
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 16일팟캐스트From $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Product진행자 Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.모델과 학습파인튜닝Pretraining & midtraining+3
2:00:19EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 6일팟캐스트1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2진행자 Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…모델과 학습Synthetic dataData quality & curation+3
1:25:35EN
Cognitive Revolution "How AI Changes Everything"· 2023년 5월 21일팟캐스트Two and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical School진행자 Nathan LabenzVivek Natarajan walks Nathan Labenz through Med-PaLM and Med-PaLM 2: the data-light techniques, the nine-axis clinician evals, and why a high USMLE-style score is the wrong trophy.모델과 학습AI in healthcare파인튜닝+3
42:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 5월 18일팟캐스트 · 2명Ten Percent of Search Is Health — and the Doctor Is Googling Too진행자 Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.모델과 학습AI in healthcare안전과 거버넌스+3
슬라이드5:24EN
MBMatthew Berman· 2023년 5월 12일Google I/O 2023: Bard, PaLM 2 and AI Across Google's ProductsMatthew Berman · Forward FutureMatthew Berman reviews Google's 2023 AI announcements and weighs its focus on improving established products.AI Strategy제품과 UX모델과 학습+1
4:14:33EN
Lex Fridman· 2023년 5월 9일팟캐스트 · 2명The Next Token Is Not a Proof: Stephen Wolfram on ChatGPT and Computational Truth게스트 Stephen Wolfram · 진행자 Lex FridmanIn his fourth conversation with Lex Fridman, Stephen Wolfram contrasts large language models with Wolfram|Alpha, then follows computational irreducibility from ChatGPT through observers, thermodynamics, and the three great theories of twentieth-century physics.모델과 학습PhilosophyAI research+3
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 4월 6일팟캐스트 · 2명A 6-Billion-Parameter Clone of ChatGPT’s Core Trick진행자 Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.모델과 학습Open-weight models파인튜닝+3
3:28:47EN
Lex Fridman· 2022년 10월 29일팟캐스트 · 2명Karpathy Calls Trained Neural Nets Complicated Alien Artifacts게스트 Andrej Karpathy · 진행자 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.모델과 학습AGI(범용 인공지능)Autonomous Driving+3
2:10:08EN
Lex Fridman· 2022년 7월 26일팟캐스트 · 2명Gato Is Only the Beginning게스트 Oriol Vinyals · 진행자 Lex FridmanDeepMind's Oriol Vinyals talks with Lex Fridman about generalist agents, thrown-away weights, and whether human-level AGI arrives in his lifetime.모델과 학습AGI(범용 인공지능)AI research+3
2:10:39EN
Lex Fridman· 2022년 7월 1일팟캐스트 · 2명Demis Hassabis: Solve Intelligence, Then Solve Everything Else게스트 Demis Hassabis · 진행자 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.모델과 학습AI researchAGI(범용 인공지능)+3
2:45:10EN
Lex Fridman· 2022년 1월 22일팟캐스트 · 2명A Teenager Learns to Drive in Twenty Hours. A Car Still Cannot.게스트 Yann Lecun · 진행자 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.모델과 학습World modelsComputer Vision+3
2:31:57EN
Lex Fridman· 2021년 9월 20일팟캐스트 · 2명Jay McClelland on How Thought Emerges From Neural Networks게스트 Jay McClelland · 진행자 Lex FridmanThe Stanford cognitive scientist talks with Lex Fridman about connectionism, backpropagation, David Rumelhart, and why intuition discovers what logic later proves.모델과 학습머신러닝 기초Deep Learning+3
2:51:33EN
Lex Fridman· 2021년 8월 29일팟캐스트 · 2명The Self Is a GPT Prompt: Wojciech Zaremba on Consciousness, Codex, and Fermi's Silence게스트 Wojciech Zaremba · 진행자 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.모델과 학습코딩 에이전트머신러닝 기초+3
2:18:29EN
Lex Fridman· 2021년 8월 8일팟캐스트 · 2명Your Cortex Is 150,000 Brains Voting on a Coffee Cup게스트 Jeff Hawkins · 진행자 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.모델과 학습Neuroscience & AI머신러닝 기초+3
2:30:30EN
Lex Fridman· 2021년 7월 31일팟캐스트 · 2명The Fallacy of the Successful First Step게스트 Ishan Misra · 진행자 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.모델과 학습Computer VisionMultimodal AI+3
1:56:17EN
Lex Fridman· 2021년 4월 19일팟캐스트 · 2명If You Reran Earth a Million Times, Would Anything Like Us Appear?게스트 Risto Miikkulainen · 진행자 Lex FridmanRisto Miikkulainen on neuroevolution, hyena raids, basil that never sleeps, and why variation-plus-selection still finds solutions backpropagation cannot see.모델과 학습머신러닝 기초AI research+3
2:01:07EN
Lex Fridman· 2020년 12월 12일팟캐스트 · 2명Michael Littman isn’t waiting for a runaway god. He’s watching us.게스트 Michael Littman · 진행자 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.모델과 학습Reinforcement LearningAGI(범용 인공지능)+3
2:10:06EN
Lex Fridman· 2020년 8월 14일팟캐스트 · 2명You Might Have to Understand the World to Understand the Letter A게스트 Dileep George · 진행자 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.모델과 학습Neuroscience & AIWorld models+3
더 보기248개 중 24개 표시