Research
Scaling Laws: Why Bigger Models Eventually Stop Improving
In 2020, researchers discovered a "physics of AI" known as Scaling Laws. Empirical observation showed that model performance improves predictably as you increase compute, parameter count, and data size. However, recent evidence suggests we are hitting diminishing returns, where adding more compute yields smaller and smaller gains, forcing the industry to look beyond raw scale.