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58:46EN
Unsupervised Learning: With Jacob Effron· 9 abr 2026PódcastTwo Dates from OpenAI's Chief Scientist: Intern by September, Automated Researcher by 2028Presenta: 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.
5:06:18EN
Lex Fridman· 2 feb 2025PódcastDeepSeek's $5 million training claim and the five-year bet on computePresenta: 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· 12 nov 2024PódcastHe bet company equity that Transformer would last — then drew an AI map for 12,000 companiesPresenta: 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"· 30 oct 2024PódcastMMLU Stays at Chance Until Late Training. Loss Is Only an Alarm.Presenta: 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"· 13 abr 2024PódcastGPT-5 Wants 100 Trillion Tokens. Does Earth Have Enough?Presenta: 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"· 6 jul 2023PódcastThe AI Scouting Report: 90 Minutes From GPT-4's Exam Scores to Whether Models UnderstandPresenta: 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"· 16 jun 2023PódcastFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductPresenta: Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.