> Biological cognition is based on network processing, too. No problem here --- it is in the "NN ideas" that I think is necessary. However, it doesn't only belong to neural network, in the technical sense. Both Novamente and NARS do network processing, in the broad sense.
> Because you're reading this message in realtime NNs are clearly a quite > powerful model. In fact, since we don't have any human-equivalent symbolic > processing systems, the burden of proof is reversed. I've addressed the difference between the natural NN and the artificial NN. Do you mean that ANN is already "human-equivalent"? > The space of automata networks is vast and almost utterly barren. > The probability of hitting a fertile spot with an educated guess > is basically nil. Of course biological tissue processing does some > fancy tricks ANNs can't yet. An approach of research is not necessarily more fruitful than the others just because in it there are more unexplored possibilities. > There won't be any AGI on any current memory-starved, few-threaded > hardware. Of course, the current hardware is not designed for the purpose of AGI, and any successful theory will even lead to new hardware, which will support more powerful systems. However, I haven't seen any convincing argument that lead me to agree that the key to AGI is new hardware design. Actually, all the previous attempts on that direction lead me to belief that without a good theory, people don't even know what hardware is needed for intelligence, except simple ideas like "massive parallel processing, huge amount of memory, and superfast CPUs", which I all agree, but there are simply not enough to answer all the questions about intelligence. Pei ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
