Re: predicts increasing hybridisation between classic supercomputers and AI
ML/AI (please stop using the term AI as its just a sales term) seems to be solving 'innovative' problems. But only when its hand-fed curated previously successful answers (so really you've just pruned the search space to make analysis tractable).
That doesn't seem quite right. The whole point of ML is to be able to generalise beyond the training set (i.e., curated data with successful answers); it would be completely useless if it didn't do that! Note that the "search space" in e.g., an ANN is the set of network weights. This search space is not "pruned"; rather, it is optimised with respect to the training data, usually via standard (and usually deterministic) algorithms such as backprop. Hopefully, the optimised set of weights then generalises well beyond the training set, in the sense that it doesn't over- or underfit new (uncurated) data that it hasn't seen before. That is the "learning" part in ML.
Biting the hand that feeds IT
