絞り込み結果
70 件並び順
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月6日ポッドキャストThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models Understandホスト 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.
1:32:22ENCognitive Revolution "How AI Changes Everything"· 2023年6月29日ポッドキャストA Million Bytes and 256 Symbols: Meta's MEGABYTE Wants to Throw the Tokenizer Awayホスト 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.
5:47EN
Matthew Berman· 2023年4月19日Sam Altman on Scaling AI Models: Matthew Berman Examines OpenAI’s 2023 DirectionMatthew Berman · Forward FutureA 2023 discussion of model scaling, possible ways to improve GPT-4 and the safety priorities OpenAI described at the time.
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年4月6日ポッドキャスト · 2 人A 6-Billion-Parameter Clone of ChatGPT’s Core Trickホスト 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.
45:03ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年2月16日ポッドキャスト · 2 人Emad Mostaque’s bet: open small models, not one giant brainホスト Sarah Guo, Elad GilStability AI’s founder tells No Priors why foundation models should be public infrastructure, why small models can beat giant ones, and what that means for media, medicine, and AGI.
1:00:36ENNo Priors: AI, Machine Learning, Tech, & Startups· 2023年2月2日ポッドキャスト · 2 人Forty games of Diplomacy, and nobody spotted the bot: Noam Brown’s 100,000x lessonホスト Sarah Guo, Elad GilMeta’s Noam Brown tells Sarah Guo and Elad Gil how Cicero negotiated in English for 40 games on a tiny web community — and why thinking at decision time beat three years of scaling.
1:36:11EN
Lex Fridman· 2022年9月17日ポッドキャスト · 2 人2029 Passes the Turing Test. 2045 Is Still the Singularityゲスト Ray Kurzweil · ホスト Lex FridmanRay Kurzweil tells Lex Fridman why his dates have not moved, how to invent in the present tense, and why the replica of his father answered the meaning of life with one word: love.
1:29:10ENLex Fridman· 2020年2月20日ポッドキャスト · 2 人Andrew Ng: The Hardest Part of AI Is Rarely the Algorithmゲスト Andrew Ng · ホスト Lex FridmanIn a conversation with Lex Fridman, Ng traces a path from late-night Coursera recordings to factory floors, arguing that messy data, habits, and starting small matter more than hype.
26:02ENLex Fridman· 2020年2月9日ポッドキャストMoore’s Law Is Not Dead—It Is a Cascade of S-Curvesホスト Lex FridmanJim Keller explains why transistor scaling keeps outrunning its obituary, and how exponential hardware changes the mathematics AI can attempt.
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.
1:14:59EN
Lenny's PodcastポッドキャストWhy Anthropic's Ben Mann Thinks the Exponential Hasn't Slowed, and Why He Still Worries About Safetyホスト Lenny RachitskyThe Anthropic co-founder on the AI talent war, scaling laws, the economic Turing test, jobs, leaving OpenAI, constitutional AI and how he forecasts the risk of superintelligence.
1:19:48ENLex FridmanポッドキャストBigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep Learningホスト Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.
1:13:40ENUnsupervised Learning: With Jacob EffronポッドキャストThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Momentホスト Jacob EffronVincent, a distinguished engineer at Waymo, explains how foundation models became teachers for self-driving, why the long tail and causality are the real frontier, and where robotics still lacks its generalist proof point.
52:28ENLex Fridmanポッドキャスト · 2 人Ray Kurzweil on Hierarchies, the Neocortex and Merging with AIゲスト Ray Kurzweil · ホスト 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.