필터 결과
14개정렬
1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026년 10월 9일팟캐스트 · 2명10,000 GB300s for Four Weeks: Reflection’s Open-Model Ledger진행자 Sarah Guo, Elad GilMisha Laskin tells No Priors how Reflection trained Beam, why reinforcement learning outspent pre-training, and why the West needs its own open weights.
49:12EN
Sequoia Capital· 2026년 7월 29일팟캐스트The People Writing the Transformer’s Eulogy Want a Lab That Can Take Vacation Without Themo1’s reasoning lead and a Gemini pre-training lead argue the architecture, not more scale, is now the bottleneck — and that replacing it starts with automating kernel generation.
58:46EN
Unsupervised Learning: With Jacob Effron· 2026년 4월 9일팟캐스트Two Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028진행자 Jacob EffronJakub Pachocki tells Jacob Effron why those timelines still hold, why continual learning is not a detour, and why showing chain of thought in the product would train the monitor away.
1:01:38ENSequoia Capital· 2026년 1월 6일팟캐스트13-Hour Coffee and 2x Throughput: Physical Intelligence Crosses the Deployment LineKarol Hausman and Tobi Springenberg tell Sequoia’s Training Data how a general robot brain, plus real-world RL, turned coffee, laundry, and chocolate boxes into jobs that actually run.
48:51ENSequoia Capital· 2025년 6월 17일팟캐스트The Breakthroughs for AGI Are Already Done, Says OpenAI’s Former Research HeadBob McGrew tells Sequoia’s Training Data that 2025 is the year of reasoning, agents will be priced at the cost of compute, and nothing fundamental will be added to the stack by 2035.
58:11ENSequoia Capital· 2025년 4월 15일팟캐스트Patrick Hsu Wants an App Store for Biology, Not Just Better DrugsThe Arc Institute co-founder argues that Evo 2, trained on genomes rather than proteins, should underpin tools for every step of the scientific method.
5:06:18EN
Lex Fridman· 2025년 2월 2일팟캐스트DeepSeek's $5 million training claim and the five-year bet on compute진행자 Lex FridmanDylan Patel and Nathan Lambert walk Lex Fridman through DeepSeek-V3 and R1, export controls, TSMC, megaclusters, and who actually makes money in the AI race.
1:04:54ENUnsupervised Learning: With Jacob Effron· 2024년 11월 12일팟캐스트He bet company equity that Transformer would last — then drew an AI map for 12,000 companies진행자 Jacob EffronDatabricks chief AI scientist Jonathan Frankle tells enterprises when to prompt, fine-tune, or pre-train, and why he still refuses to forecast the next architecture.
2:24:18EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 30일팟캐스트MMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.진행자 Nathan LabenzZyphra’s training lead walks through Zamba 2’s hybrid architecture, the evals that actually matter, and the trade secrets small labs still have to rediscover.
46:09ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024년 8월 1일팟캐스트 · 2명Oriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are Numbered진행자 Sarah Guo, Elad GilGoogle DeepMind’s VP of research on Gemini, long context, the coming shift from pretraining to RL, and why AGI may never have a finish line.
1:01:39ENCognitive Revolution "How AI Changes Everything"· 2024년 4월 13일팟캐스트GPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?진행자 Nathan LabenzTraining GPT-3 took about a trillion tokens; GPT-4 took about ten trillion. The next jump is a data question as much as a compute one.
1:33:56ENCognitive 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.
59:28ENCognitive 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.
2:23:56ENLex Fridman· 2023년 3월 25일팟캐스트 · 2명GPT-4 is a very early AI. ChatGPT is the line in the history books게스트 Sam Altman · 진행자 Lex FridmanSix days after GPT-4 shipped, Sam Altman tells Lex Fridman why usability beat raw scale, why alignment and capability are not opposite vectors, and why OpenAI is trying to deploy while the stakes are still low.