The podcast examines the progress in open model development, highlighting models like Qwen 3.8 and Kimi K3, and discusses challenges in benchmarking, distillation, and post-training fine-tuning. It notes the growing infrastructure and economic incentives in China, with significant investments in labs and the impact of chip smuggling. The open ecosystem is expected to expand, driven by the potential of open models in niche tasks and future advancements, while emphasizing the importance of capital efficiency and resource allocation.
Reflections on AI's writing ability and how AI models get more capable.

After a few long years of finding time to document my lessons from training open models, my post-training book is done!

Musings on model alignment, what determines safety, and where we go from here.
