lorien@dartvax.UUCP (09/19/83)
The Parallelism and AI projects at the University of Maryland sound very
interesting. I agree with an article posted a few days back that
parallel hardware won't necessarily produce any significantly new methods
of computing, as we've been running parallel virtual machines all along.
Parallel hardware is another milestone along the road to "thinking in parallel",
however, getting away from the purely Von Neumann thinking that's done in
the DP world these days. It's always seemed silly to me that our computers
are so serial when our brains: the primary analogy we have for "thinking
machines" are so obviously parallel mechanisms. Finally we have the technology
(software AND hardware) to follow in our machine architecture cognitive
concepts that evolution has already found most powerful.
I feel that the sector of the Artificial Intelligence community that pays
close attention to psychology and the workings of the human brain deserves
more attention these days, as we move from writing AI programs that "work"
(and don't get me wrong, they work very well!) to those that have
generalizable theoretical basis. One of these years, and better sooner
than later, we'll make a quantum leap in AI research and articulate some
of the fundamental structures and methods that are used for thinking.
These may or may not be isomorphic to human thinking, but in either case
we'll do well to look to the human brain for inspiration.
I'd like to hear more about the work at the University of Maryland; in
particular the prolog and the parallel-vision projects.
What do you think of the debate between what I'll call the Hofstadter
viewpoint: that we should think long term about the future of artificial
intelligence, and the Feigenbaum credo: that we should stop philosophizing
and build something that works? (Apologies to you both if I've misquoted)
--Lorien Y. Pratt
decvax!dartvax!lorien
(Dartmouth College)