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Chapters
Read from the show notes
- 0:00 Introduction
- 1:39 Sponsors, Comments, and Reflections
- 16:29 China vs US: Who wins the AI race?
- 25:11 ChatGPT vs Claude vs Gemini vs Grok: Who is winning?
- 36:11 Best AI for coding
- 43:02 Open Source vs Closed Source LLMs
- 54:41 Transformers: Evolution of LLMs since 2019
- 1:02:38 AI Scaling Laws: Are they dead or still holding?
- 1:18:45 How AI is trained: Pre-training, Mid-training, and Post-training
- 1:51:51 Post-training explained: Exciting new research directions in LLMs
- 2:12:43 Advice for beginners on how to get into AI development & research
- 2:35:36 Work culture in AI (72+ hour weeks)
- 2:39:22 Silicon Valley bubble
- 2:43:19 Text diffusion models and other new research directions
- 2:49:01 Tool use
- 2:53:17 Continual learning
- 2:58:39 Long context
- 3:04:54 Robotics
- 3:14:04 Timeline to AGI
- 3:21:20 Will AI replace programmers?
- 3:39:51 Is the dream of AGI dying?
- 3:46:40 How AI will make money?
- 3:51:02 Big acquisitions in 2026
- 3:55:34 Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta
- 4:08:08 Manhattan Project for AI
- 4:14:42 Future of NVIDIA, GPUs, and AI compute clusters
- 4:22:48 Future of human civilization
Not from the publisher — times may be approximate.
Show notes
Nathan Lambert and Sebastian Raschka are machine learning researchers, engineers, and educators. Nathan is the post-training lead at the Allen Institute for AI (Ai2) and the author of The RLHF Book. Sebastian Raschka is the author of Build a Large Language Model (From Scratch) and Build a Reasoning Model (From Scratch). Thank you for listening ❤ Check out our sponsors: [https://lexfridman.com/sponsors/ep490-sc]( https://lexfridman.com/sponsors/ep490-sc">https://lexfridman.com/sponsors/ep490-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. **Transcript:** [https://lexfridman.com/ai-sota-2026-transcript]( https://lexfridman.com/ai-sota-2026-transcript">https://lexfridman.com/ai-sota-2026-transcript **CONTACT LEX:** **Feedback** – give feedback to Lex: [https://lexfridman.com/survey]( https://lexfridman.com/survey">https://lexfridman.com/survey **AMA** – submit questions, videos or call-in: [https://lexfridman.com/ama]( https://lexfridman.com/ama">https://lexfridman.com/ama **Hiring** – join our team: [https://lexfridman.com/hiring]( https://lexfridman.com/hiring">https://lexfridman.com/hiring **Other** – other ways to get in touch: [https://lexfridman.com/contact]( https://lexfridman.com/contact">https://lexfridman.com/contact **SPONSORS:** To support this podcast, check out our sponsors & get discounts: **Box:** Intelligent content management platform. Go to [https://box.com/ai]( https://lexfridman.com/s/box-ep490-sc">https://box.com/ai **Quo:** Phone system (calls, texts, contacts) for businesses. Go to [https://quo.com/lex]( https://lexfridman.com/s/quo-ep490-sc">https://quo.com/lex **UPLIFT Desk:** Standing desks and office ergonomics. Go to [https://upliftdesk.com/lex]( https://lexfridman.com/s/uplift\_desk-ep490-sc">https://upliftdesk.com/lex **Fin:** AI agent for customer service. Go to [https://fin.ai/lex]( https://lexfridman.com/s/fin-ep490-sc">https://fin.ai/lex **Shopify:** Sell stuff online. Go to [https://shopify.com/lex]( https://lexfridman.com/s/shopify-ep490-sc">https://shopify.com/lex **CodeRabbit:** AI-powered code reviews. Go to [https://coderabbit.ai/lex]( https://lexfridman.com/s/coderabbit-ep490-sc">https://coderabbit.ai/lex **LMNT:** Zero-sugar electrolyte drink mix. Go to [https://drinkLMNT.com/lex]( https://lexfridman.com/s/lmnt-ep490-sc">https://drinkLMNT.com/lex **Perplexity:** AI-powered answer engine. Go to [https://perplexity.ai/]( https://lexfridman.com/s/perplexity-ep490-sc">https://perplexity.ai/ **OUTLINE:** (00:00) – Introduction (01:39) – Sponsors, Comments, and Reflections (16:29) – China vs US: Who wins the AI race? (25:11) – ChatGPT vs Claude vs Gemini vs Grok: Who is winning? (36:11) – Best AI for coding (43:02) – Open Source vs Closed Source LLMs (54:41) – Transformers: Evolution of LLMs since 2019 (1:02:38) – AI Scaling Laws: Are they dead or still holding? (1:18:45) – How AI is trained: Pre-training, Mid-training, and Post-training (1:51:51) – Post-training explained: Exciting new research directions in LLMs (2:12:43) – Advice for beginners on how to get into AI development & research (2:35:36) – Work culture in AI (72+ hour weeks) (2:39:22) – Silicon Valley bubble (2:43:19) – Text diffusion models and other new research directions (2:49:01) – Tool use (2:53:17) – Continual learning (2:58:39) – Long context (3:04:54) – Robotics (3:14:04) – Timeline to AGI (3:21:20) – Will AI replace programmers? (3:39:51) – Is the dream of AGI dying? (3:46:40) – How AI will make money? (3:51:02) – Big acquisitions in 2026 (3:55:34) – Future of OpenAI, Anthropic, Google DeepMind, xAI, Meta (4:08:08) – Manhattan Project for AI (4:14:42) – Future of NVIDIA, GPUs, and AI compute clusters (4:22:48) – Future of human civilization