Here's my conversation all about AI in 2026, including technical breakthroughs, scaling laws, closed & open LLMs, programming & dev tooling (Claude Code, Cursor, etc), China vs US competition, training pipeline details (pre-, mid-, post-training), rapid evolution of LLMs, work culture, diffusion, robotics, tool use, compute (GPUs, TPUs, clusters), continual learning, long context, AGI timelines (including how stuff might go wrong), advice for beginners, education, a LOT of discussion about the future, and other topics.

It's a great honor and pleasure for me to be able to do this kind of episode with two of my favorite people in the AI community: Sebastian Raschka, PhD and Nathan Lambert. They are both widely-respected machine learning researchers & engineers who also happen to be great communicators, educators, writers, and X posters.

This was a whirlwind conversation: everything from the super-technical to the super-fun.