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Unsupervised Learning: With Jacob Effron· Apr 9, 2026PodcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Host 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.
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Lex Fridman· Feb 2, 2025PodcastDeepSeek's $5 million training claim and the five-year bet on computeHost 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· Nov 12, 2024PodcastHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesHost 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.
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Cognitive Revolution "How AI Changes Everything"· Oct 30, 2024PodcastMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.Host 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.
1:01:39ENCognitive Revolution "How AI Changes Everything"· Apr 13, 2024PodcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Host 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"· Jul 6, 2023PodcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandHost 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"· Jun 16, 2023PodcastFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductHost Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.