#AI scalability

KI-Pioneer Sutton calls synthetic data a "big mistake" in the face of an infinitely complex world

This article explores Richard Sutton's critique of synthetic data in AI, arguing that the infinite complexity of the real world cannot be adequately captured by artificial datasets. It examines the Big World Hypothesis and proposes continual learning agents as a more scalable alternative.