February 2026 – RadCasts

A second woman has alleged she was sent to Britain by the late sex offender, Jeffrey Epstein, to have sex with Andrew Mountbatten-Windsor who has always denied wrongdoing. Also: there are explosions in Iran amid heightened tensions; a US federal judge allows ICE to continue the immigration crackdown in Minnesota; Pakistan's army kills rebels in Balochistan province; European and non-English movies gain momentum ahead of the Oscars; the ethics of AI creating life; and do dogs need clothing?

The Global News Podcast brings you the breaking news you need to hear, as it happens. Listen for the latest headlines and current affairs from around the world. Politics, economics, climate, business, technology, health – we cover it all with expert analysis and insight.

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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
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Transcript:
https://lexfridman.com/ai-sota-2026-transcript

CONTACT LEX:
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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

Month: February 2026

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Lex Fridman Podcast - #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI