Scientific feedback reveals productive regimes beyond training conventions
The research shows that scientific feedback can guide AI models to discover better designs than those they were trained on, even when those designs violate implicit rules. By using performance feedback in reactor design and chemical reactions, the model adapted its search strategy to find more productive alternatives outside its initial training boundaries.