That actually raises a more fundamental question here. This project specifically focused their tests on research topics that can feasibly be tested by the ML t

That actually raises a more fundamental question here. This project specifically focused their tests on research topics that can feasibly be tested by the ML tools, writing software. I assume that was an intentional decision, and a clever one that let them point to promising test results while ignoring that potential limitation when valuing their tool. These ML tools will need to not only come up with novel ideas, they'll need a way to test and validate them. For anything outside of software that almost certainly means modelling. If we already have validated models that may work well enough, but if you extend the scope to literally any novel protein that is possible the ML tool would first have to figure out how to model it. What would that even look like? How would an ML tool trapped in a computer and limited to the knowledge it was trained on be able to model any protein in the universe and be able to validate exactly how it would function in the real world?