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1:09:44EN
No Priors: AI, Machine Learning, Tech, & Startups· 9. Okt. 2026Podcast · 2 Stimmen10,000 GB300s for Four Weeks: Reflection’s Open-Model LedgerModeration: 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.Open Source & CommunityOpen-weight modelsReinforcement Learning+3
49:12EN
Sequoia Capital· 29. Juli 2026PodcastThe 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.Modelle & TrainingAI researchPretraining & midtraining+3
58:46EN
Unsupervised Learning: With Jacob Effron· 9. Apr. 2026PodcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Moderation: 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.Modelle & TrainingContinual learningReinforcement Learning+3
1:01:38EN
Sequoia Capital· 6. Jan. 2026Podcast13-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.Modelle & TrainingRoboticsReinforcement Learning+3
48:51EN
Sequoia Capital· 17. Juni 2025PodcastThe 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.Modelle & TrainingReasoning & test-time computePretraining & midtraining+3
58:11EN
Sequoia Capital· 15. Apr. 2025PodcastPatrick 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.Modelle & TrainingAI for sciencePretraining & midtraining+3
5:06:18EN
Lex Fridman· 2. Feb. 2025PodcastDeepSeek's $5 million training claim and the five-year bet on computeModeration: 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.Unternehmen & StrategieOpen-weight modelsPretraining & midtraining+3
1:04:54EN
Unsupervised Learning: With Jacob Effron· 12. Nov. 2024PodcastHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesModeration: 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.Unternehmen & StrategieTransformers & attentionPretraining & midtraining+3
2:24:18EN
Cognitive Revolution "How AI Changes Everything"· 30. Okt. 2024PodcastMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.Moderation: 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.Modelle & TrainingLocal inferenceEvals+3
46:09EN
No Priors: AI, Machine Learning, Tech, & Startups· 1. Aug. 2024Podcast · 2 StimmenOriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are NumberedModeration: 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.Modelle & TrainingAGI TimelinesPretraining & midtraining+3
1:01:39EN
Cognitive Revolution "How AI Changes Everything"· 13. Apr. 2024PodcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Moderation: 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.Modelle & TrainingScaling LawsSynthetic data+3
1:33:56EN
Cognitive Revolution "How AI Changes Everything"· 6. Juli 2023PodcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandModeration: 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.Modelle & TrainingML-GrundlagenScaling Laws+3
59:28EN
Cognitive Revolution "How AI Changes Everything"· 16. Juni 2023PodcastFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductModeration: Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.Modelle & TrainingFine-TuningPretraining & midtraining+3
2:23:56EN
Lex Fridman· 25. März 2023Podcast · 2 StimmenGPT-4 is a very early AI. ChatGPT is the line in the history booksGast: Sam Altman · Moderation: 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.Unternehmen & StrategiePost-trainingSicherheit & Governance+3