>They may be useful in the sense of generating commercial value, just like ML is useful to random-walking you to some solution that you couldn't have come up wi

>They may be useful in the sense of generating commercial value, just like ML is useful to random-walking you to some solution that you couldn't have come up with, but it is not science. There is little insight to be gained from this, it is more guesswork and art than anything else, and likely at some points the practical results will diminish as soon as one stumbles about more fundamental problems and has no model or structure to reason with This is just normal for the scientific process, and I'd argue that ML currently is more rigorous than any of the soft sciences. The truth is that we likely need a new field of math to properly model neural networks...until then we are gleaning vast amounts of empirical but still scientific data as to the behavior of this new tech. The proof is that these nets work and are already doing amazing things.