필터 결과
19개정렬
53:44EN
Sequoia Capital· 2026년 8월 18일팟캐스트The Biggest Bug in Today’s Models Is That the Weights Never ChangeTuring Award winner Rich Sutton and Khurram Javed founded Oak Lab to build agents that keep learning after they ship — and they call synthetic data a big mistake.
38:45ENSequoia Capital· 2026년 6월 16일팟캐스트The 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
41:36ENSequoia Capital· 2025년 11월 18일팟캐스트Four Months to Drive Tokyo: How Wayve Bet the Company on One End-to-End NetworkWayve CEO Alex Kendall tells Sequoia’s Training Data why AV 2.0 ditches HD maps and hand-written stacks for a foundation model that can adapt to a new car and a new country in weeks.
32:59EN
No Priors: AI, Machine Learning, Tech, & Startups· 2025년 7월 24일팟캐스트 · 2명A Hundred People, a Billion in Revenue, and Zero Venture Money진행자 Sarah Guo, Elad GilSurge AI founder Edwin Chen on why quality human data is a poetry problem, not a bounding-box problem, and why leaderboards keep training models to write clickbait.
45:21ENNo Priors: AI, Machine Learning, Tech, & Startups· 2025년 6월 17일팟캐스트 · 2명Applied Intuition Is Worth $15 Billion, Hasn't Spent Its Capital, and Wants to Be the OS for Cars and Tanks진행자 Sarah Guo, Elad GilOn No Priors, Qasar Younis and Peter Ludwig explain the Microsoft playbook for vehicles, why they waited for autonomy techniques to converge, and why Waymo's business model is the question that follows the demo.
38:25ENSequoia Capital· 2025년 5월 27일팟캐스트A thousand airplanes will never train an AI engineerFormer Airbus CTO Paul Eremenko explains why physical-world engineering still has no coding-AI moment, and how P-1 AI's agent Archie is supposed to get there anyway.
55:40ENSequoia Capital· 2025년 4월 29일팟캐스트To Solve All Diseases, Isomorphic Labs Needs a Half-Dozen AlphaFoldsMax Jaderberg on turning DeepMind's game-playing research into a general AI engine for drug design—and why prediction alone cannot search a 10^60 molecular universe.
51:08EN
Unsupervised Learning: With Jacob Effron· 2025년 4월 15일팟캐스트The Transformer Co-Author Who Says Scaling Hit a Wall진행자 Jacob EffronCohere CEO Aidan Gomez tells Redpoint that a $100 million model is still an amnesiac genius, and that enterprise AI money is concentrating in support, research, and the back office.
52:30ENSequoia Capital· 2025년 1월 28일팟캐스트Move 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 2일팟캐스트30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think진행자 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.
39:45ENSequoia Capital· 2024년 9월 24일팟캐스트Harmonic’s Bet: Teach AI Math Directly, and the Riemann Hypothesis Falls by 2029Robinhood’s Vlad Tenev and Harmonic co-founder Tudor Achim tell Sequoia why math is reasoning, why Lean is the verifier, and why they refuse to wait for mathematical skill to emerge from scale.
44:16ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024년 9월 5일팟캐스트 · 2명A perfect demo is ten years from a product you can pay for진행자 Sarah Guo, Elad GilAndrej Karpathy uses Waymo's decade-long gap, Tesla's software bet, and a new AI course to argue that autonomous intelligence will stall at product and globalization, not at the first impressive clip.
39:00ENNo Priors: AI, Machine Learning, Tech, & Startups· 2024년 5월 22일팟캐스트 · 2명JPMorgan Has 150 Petabytes. GPT-4 Trained on Less Than One.진행자 Sarah Guo, Elad GilScale AI founder Alexandr Wang tells No Priors why easy internet data is exhausted, why expert-plus-model teams still win, and why the path to AGI looks more like curing cancer than inventing a vaccine.
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.
1:21:50ENCognitive Revolution "How AI Changes Everything"· 2023년 11월 14일팟캐스트A 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.진행자 Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.
1:17:09ENCognitive Revolution "How AI Changes Everything"· 2023년 9월 26일팟캐스트GPT-4 as Teacher, GPT-3.5 as Student: A Nine-Tenths Cost Cut and an AI Bundle Nobody Will Start진행자 Nathan LabenzNathan Labenz reports that chain-of-thought traces from GPT-4 train a cheaper, faster 3.5, then argues for flooring the app accelerator, tapping the brake on GPT-5, and bundling a hundred AI tools for a hundred dollars.
3:11:35EN
Lex Fridman· 2023년 6월 21일팟캐스트 · 2명Search was always a hack: Marc Andreessen on AI, truth, and the next internet게스트 Marc Andreessen · 진행자 Lex FridmanLex Fridman sits down with the Mosaic co-creator and Andreessen Horowitz founder to ask whether Google Search, the browser, and open-source AI survive the decade.
2:00:19ENCognitive 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…
1:14:34EN
Lenny's Podcast팟캐스트 · 2명Inside the Frontier Lab: How Karina Nguyen Builds Products by Training the Model게스트 Karina Nguyen · 진행자 Lenny RachitskyOpenAI researcher Karina Nguyen explains synthetic data, evals, how Canvas and Tasks were made, and which human skills matter as models get smarter.