>This is a rather intuitive mathematical proof that neural nets can emulate all functions in many dimensions. Yes, but the problem is we don't know what functi

>This is a rather intuitive mathematical proof that neural nets can emulate all functions in many dimensions. Yes, but the problem is we don't know what function we want to approximate. So it is like interpolation you give it some points and you get an approximation that is good enough around those points but probably very wrong if you are far away of the points. We don't even know how many layers and neurons are needed so it seems to be a brute force approach, throw more data and more hardware and when stuff goes wrong maybe throw more data. But one day a Tesla might go on a different environment and maybe people have different hats and goes to shit because those hats were not in the training data, we don't have like in other sciences bounded errors.