you're conflating two different disciplines: distributed protein folding studies the biophysical process of proteins folding over time, while protein structure prediction makes a static single predict of what is believed to be the final structure adopted by the protein in the folding process.

I think many people believe that given infinite computer time the protein folding simulations would produce the same output as the static prediction (modulo a number of complex details) but use far, far more computer time to get there.

The fundamental observation from the DM AF2 paper that I've been able to glean (which I kind of sort of already believed) is that careful multiple sequence alignments of 30-100 evolutionarily related proteins is enough to produce coarse distance constraints that can be used to guide a structure prediction to a good answer quickly. And that depended on new ML technology that didn't exist before.