The flaw (geddit?) in this is that deep networks are processing data from different domains, with different characteristics (which change in chaotic ways). In ML the choice was always "the simpler the better" - we used statistics and information theory to apply Occam's razor. Deep networks don't work that way and they do work well in some real domains, nature does not always prefer simple domain theories. If the laws of the universe suddenly changed designing optics would suddenly be difficult as well.