We have a pretty poor understanding of how the human brain (our only "Strong AI" evidence) learns, but the one approach that has been pretty definitively ruled out is large-scale backpropagation in the style that most deep learning pursues today. Maybe backprop is a true alternative approach to AGI, but it's hard to be completely convinced of this.
I haven’t finished reading it, but they make the case that if humans are conscious, then PDP is the way Strong AI will be figured out.
https://mitpress.mit.edu/books/parallel-distributed-processi...
I agree that there’s too much emphasis on the “robot”, but coming from an academic background in mathematics and psychology (and biology), I cannot take PDP as anything other than “this is how brains work”. Granted, half of PDP, the book, is a series of examples of “ways it might work” from 40 years ago or so, but the other half is about fundamentally tying the psychology to the brain through parallel distributed processing as a conceptual framework.
In that sense, I don’t think PDP can be refuted any more than token economies or political polling can be refuted.
Thoughts?
In the meantime, I will bookmark your thesis for perusal.