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Lex Fridman Podcast

State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI

Lex Fridman Podcast

#490 · Introduction
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10 min
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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: lexfridman.com/sponsors/ep490-sc See below for , transcript, and to give feedback, submit questions, contact Lex, etc.

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

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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