I understand where you're coming from and also agree in principle, but I'd change the claim that "this approach is just not enough" with "this approach is just

I understand where you're coming from and also agree in principle, but I'd change the claim that "this approach is just not enough" with "this approach is just not enough for achieving many things in machine learning including breaking new ground". I think there's always a way to be creative within the constraints and concepts/axioms you take as given. For example, the fact that I have absolutely no control (or knowledge for that matter) on how to design or improve the microprocessor on my computer, I don't feel this is limiting my creativity in software development at all. Once changes and improvements occur in the hardware level, I'm sure they will find a way to the software development layer and then I'll be handed even more degrees of freedom to be creative (though I'm not complaining with the freedom I currently have). Don't you think the same might apply to machine learning - i.e those with solid theoretical/mathematical background are analogous to the chip designers and the "machine language hackers" are the software developers?