It seems you don't understand the difference between a mathematical construct that can hold and process information and the information stored within it. Neural networks are a mathematical approximation to biological neural systems, an extraction of the fundamental mathematical behaviour, without the biologically imperfect representation of those rules. True, some of the current networks miss certain functions, however they can approximate them. This was been mathematically proven back in the 80s (though practically it is inefficient).
The first step in mirroring true intelligent AI is the development of the fundamental mathematical construct, the second is identifying how to assemble the elements of that construct into increasingly complex and capable systems. We are at the early stages of the 2nd part of this process. It is very primitive AI.
Declaring that you think processing a 3D model's vertices is in any way equivalent to processing a neural model just because they require the same mathematical operation at some a point in the calculation really demonstrates a lack of understanding of maths, modelling and the relevant domains.