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

Turing Award winner Richard Sutton calls synthetic data a "big mistake" for scaling large language models. The world is infinitely complex, and any simulation of it is "microscopic," with human expertise acting as a bottleneck that blocks real scaling. Sutton's alternative is agents that learn…

Turing Award winner Richard Sutton calls synthetic data a "big mistake" for scaling large language models. The world is infinitely complex, and any simulation of it is "microscopic," with human expertise acting as a bottleneck that blocks real scaling. Sutton's alternative is agents that learn continually from their own experience instead of relying on frozen models. The article KI-Pioneer Sutton calls synthetic data a "big mistake" in the face of an infinitely complex world appeared first on The Decoder.

Source: The Decoder — Published August 20, 2026 at 12:14 UTC — Category: Models