You raise good questions. I'm mixing two different types of models to make a point from two different directions. Each has it's own and different limitations

You raise good questions. I'm mixing two different types of models to make a point from two different directions. Each has it's own and different limitations. Deep Mind Alpha Fold did not get the rules from reading papers. It uses a combination of learned (from being trained on known protein structures) prediction of structure, and iterative application of learned refinement, constrained by physical and chemical rules. So, some of the knowledge required is "programmed in" as you suggest, but most has been learned by the algorithm through training on known structures. My point was that the result is nevertheless a workable effective procedure for predicting protein structures. The other system that I referred to did learn from reading literature. It is a fundamentally different AI architecture (a variant of transformer architecture for large language models). It has no physical knowledge programmed in.