This article is mis-titled. The ORNL project seems to be entirely about optimizing DNN hyperparameters (like Google's AutoML, I think), and not about inventing novel DNN architectures.

Worse, the work has absolutely nothing to do with Scientific Discovery, which is a difficult and hugely ambitious area of ML study which involves generating novel induction of necessary mechanisms, not just the mostly random generation and testing of plausible patterns against outcomes.

Unless a ML method proposes hypotheses that are based on the induction of novel mechanistic principles, it ain't discovery. It's mere trial and error.

[Edited for clarity.]