Scaling Laws: O1 Pro Architecture, Reasoning Training Infrastructure, "Failures"

This is from Dec-11-2025 but offers some context on recent announcements by DeepSeek team. Excerpts from opening section

"There has been an increasing amount of fear, uncertainty and doubt (FUD) regarding AI Scaling laws. A cavalcade of part-time AI industry prognosticators have latched on to any bearish narrative they can find, declaring the end of scaling laws that have driven the rapid improvement in Large Language Model (LLM) capabilities in the last few years."

"The reality is that there are more dimensions for scaling beyond simply focusing on pre-training, which has been the sole focus of most of the part-time prognosticators. OpenAI’s o1 release has proved the utility and potential of reasoning models, opening a new unexplored dimension for scaling. This is not the only technique, however, that delivers meaningful improvements in model performance as compute is scaled up. Other areas that deliver model improvements with more compute include Synthetic Data Generation, Proximal Policy Optimization (PPO), Functional Verifiers, and other training infrastructure for reasoning. The sands of scaling are still shifting and evolving, and, with it, the entire AI development process has continued to accelerate. "