The Evolution of AI Scaling Laws: From Prediction to Reflection
How the field moved from optimizing for prediction to reward, and why the next breakthrough requires causal reasoning
The dominant narrative in ML has been one of relentless pursuit of scale. For years, the path to more capable models seemed paved with more parameters, more data, and more compute. Yet, the returns on this strategy are showing signs of diminishing.