The folding@home approach is very limited to short individual simulation times (a millisecond total, maybe, but 100 disconnected nanoseconds at a time), so it then relies on various 'enhanced sampling' techniques to try to put your thumb on the scale to bias things into exploring interesting dynamics. It seems like it is probably more effective the more you already know about a given protein target. Meta's approach (which seems like AF2, but faster/worse?) seems to have a similar problem, in that it's even less trustworthy when you apply it to a new target you have relatively little concrete information about.