Sorry to be mean but all this sounds awfully confused and terribly hand-wavy. It sounds like you think that stuff would just magically work like you want it, if only you mix up enough ingredients (data, computation, neural networks, evolution, abstractions, representations, graphs...).
Well, stuff doesn't just magickally work. Lots of people (like, literally thousands) are training machine learning models and not a single model has ever come close to "understanding" anything. I'd start from trying to figure out why that is the case, and then see if something can be done about it.
Otherwise -and, sorry again, but- all these are mere time-wasting fantasies.