On 11/2/02 9:29 AM, "Ben Goertzel" <[EMAIL PROTECTED]> wrote: > Yes, one can make plausible mathematical definitions of general > intelligence, and then prove that given arbitrarily generous computational > resources, general intelligennce is possible. Marcus Hugger and Juergen > Schmidhuber have done a great job of this in some recent papers, using > algorithmic information theory, statistical decision theory, and related > tools.
I would, at the very least, agree that most published research on the supporting mathematics is inadequate at best. This has been a (the?) major stumbling block since the beginning of computer science with respect to AI. I just think that it is a bit of "the cart before the horse" that so few people doing AI research are actually tackling the fundamental theoretical questions rather than trying to devise solutions. To a certain extent I understand it -- the glory is in the solution -- but it seems that people haven't been as lucky as they hoped. To put it another way: Even if we built a perfect model of the human brain on silicon by perfectly copying the functionality of biological neurons and their interconnections and so forth, what have we really learned? In my estimation, precious little. > But in the (real) case where one doesn't have arbitrarily generous > computational resources, there is no solid well-worked out theory to guide > one... one has to go by intuition, basically. And it's here that study of > biological intelligence may be inspirational. If one is trying to build an > intuition about how to create general intelligence using modest > computational resources, doesn't it make sense to look at the best known > example of powerful general intelligence using modest computational > resources?? [i.e. the human brain]. This doesn't mean one tries to simulate > or even closely emulate biological systems, but it does mean that the > comparison with biological systems is more than a curiosity... I don't disregard biology out of hand. I just think that copying biology without a clue as to why doesn't really solve any problems. I guess in some ways I'm less interested in building any old viable AI as I am in figuring out the fundamental science of intelligent systems. One thing we've had to deal with is that in practice my best theoretical models map closer to biological systems than I ever thought possible, particularly since they were not derived from biology. And at this point we are still doing more with less (in a design complexity sense) than any other project that I'm aware of. > Now, James, maybe you really have such a great intuition for AGI design that > you can make all the right decisions without ever looking to biosystems for > inspiration.... Time will tell, as with all our AGI attempts, eh? ;) Heh! One way or another, we'll know in a few years. :-) -James Rogers [EMAIL PROTECTED] ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/
