AI Scaling Laws: Beyond Pre-training, a New Paradigm Emerges
2024-12-12
This article explores the evolution of AI scaling laws, arguing that they extend beyond pre-training. OpenAI's o1 model demonstrates the utility and potential of reasoning models, opening a new, unexplored dimension for scaling. The article delves into techniques like synthetic data, Proximal Policy Optimization (PPO), and reinforcement learning to enhance model performance. It clarifies that Anthropic's Claude 3.5 Opus and OpenAI's Orion weren't failures, but rather shifts in scaling strategies. The authors emphasize that scaling encompasses more than just increasing data and parameters; it includes inference-time compute, more challenging evaluations, and innovations in training and inference architecture.