For sure! Another thing to note is that, at the moment, the usual ML/AI approaches fall very short of the classical optimization methods, so there is still plen

For sure! Another thing to note is that, at the moment, the usual ML/AI approaches fall very short of the classical optimization methods, so there is still plenty of work to be done. For example, classical optimization methods can approximately optimize a design with ~10 million parameters in a few hours on a decent machine, while the current AI state of the art (notably using DL and some GANs) can only optimize designs with 10-100s of parameters, maybe 1000s and take many days to train.