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

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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.

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