> I think I prefer Daniel Amit's approach, where one views NN's as the > class of nonlinear dynamical systems composed of networks of > neuron-like elements. > > Then, it becomes clear that the standard NN architectures form a very > small subclass of possible NN's....
Of course, most of the limitations of NN can be avoid by generalizing the concept to such a level. However, at the same time, such a general notion does not support the claims of advantages of NN, either. How can someone argue that this concept can compete with the classical symbolic model of cognition? Can semantic network be counted as a kind of neural network? Once again, when the extension of a concept gets larger and larger, its intension gets smaller and smaller. > As for whether NN's are the best architecture for AGI right now, I > agree that they are not. My reason is that no one knows how complex, > abstract knowledge can be efficiently, adaptably represented in NN's. > > I'm sure there *is* a way to do it, but since no has discovered it yet > (via either mathematical theory, computational experimentation, or > neuroscience), basically in my view NN-based AGI is a non-starter. Agree. > Once this conceptual problem is solved, then NN-based AGI may become a > good strategy. However, I still think it will wind up being worse > than probabilistic logic based AGI, at least on von Neumann computers > (or networks thereof), because NN architectures don't take good > advantage of the particular strengths of von Neumann computers (which > can do very precise operations very quickly in serial, a quite > different strength from the human brain, and one which is in large > part wasted when computers are used for NN computation) Don't fully agree, but that is a separate issue. Pei > ben g > -- Ben > > ------- > To unsubscribe, change your address, or temporarily deactivate your > subscription, > please go to http://v2.listbox.com/member/[EMAIL PROTECTED] > ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
