Nathan Lambert believes there is some basis for viewing distillation as a primary means by which Chinese open-source models catch up, but that this is oversimplified; he notes that post-training has now shifted to being mainly about reinforcement learning environments, and that simply using the strongest model to generate completions for SFT and watching scores rise is hard to reproduce in the open literature.