The discussion highlights the evolution of AI model training from simple SFT-based approaches to more complex, recipe-driven methods, emphasizing the role of distillation and domain-specific models. It underscores the trade-offs between simplicity and complexity, the importance of recipe diversity, and the slow but steady progress in AI research.
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.
