The mathematics of NNs are Victorian, it's just regression. The NN architecture is largely irrelevant: that only determines how easily the regression converges. The strategy is the same: just compress the data into a correlative statistical model, and estimate using statistical associations.
That's the wrong category of solution, and as a category, it's anchient. The hardware of modern digital computers is impressive, NNs are an absurd joke -- as is any correlative model of data -- a magic trick carried entirely by the performance of CPUs and HDDs.
Newton did not predict the existence of an undiscovered planet by finding correlations in the stars of the night sky. He first produced an actual theory of gravity.
Intelligence is theorising, ie., it is an explanatory process. Correlations in the frequencies of characters in books (we wrote!) is the basis for a neat trick.
There's a tremendous amount of pseudoscience in the claim that these are models of anything at all. Inasmuch as correlations in patterns of pixels in the night sky is not a model of gravity, and provides no means to "predict" anything other than pixel patterns of the night sky.