If neural nets can compute any function (as seems neatly proven here) then can they compute any function in more than a single way? If so, then upon applying the novel input (which was our goal following training) how can we know that the particular way which was computed via training set is 'right' for our novel input? If this is all true then it would seem to make neural nets perfectly unreliable as a means to modeling..?
