F. Frank LeFever wrote in message <7lr2jg$cdo at dfw-ixnews8.ix.netcom.com>...
>[commenting on Mentifex diagrams]
>I wouldn't bother looking beyond the diagrams he posts from time to
>time: they are "armchair" or "common sense" notions of how the brain
>"should" be organized that show absolutely no sign of being influenced
>by what we know of actual brain organization on the basis of
>"experiments of nature" (e.g. lesions due to stroke), formal laboratory
>studies, experimental cognitive psychology, etc., etc.
>>Seems to me I saw somebody's comment to the effect that AI systems do
>not HAVE to mimic natural systems and can stand on their own; but
>unless more novel/elegant/interesting as pure creations than these
>simplistic diagrams seem to imply, I see no point in pursuing such
>schemes even as a hobby or game...
>>F. Frank LeFever, Ph.D.
>New York Neuropsychology Group
>
I largely agree with this opinion. Some years ago, I used to think
that AI systems should pursue their own destinies, creating algorithms
without regard to their "biological" counterparts (read: us), just
by knowing what is required to make a system intelligent. This is,
in fact, the predominant working model of the majority of the AI
researchers that came from Computer Science departments.
However, it became clear to me that the problem of "intelligence" is
much, much more complex than our naive illusions led us to believe.
Today I see no point in doing anything related to AI without a
strong biological plausibility. One line of argument is that we must
follow the path of the natural intelligences until we grasp what
are the core points of intelligence, because we *still* don't know
what they are. Only after that we will be able to "propose" new
methods and algorithms to enhance biological intelligence with
functionally equivalent (but better) processes.
This does not preclude experimentation: often we'll have to create
"strange" things, based on unlikely methods. What is important is
not to lose the goal of obtaining plausible results, comparing
our results with children's ways of learning and adult's methods
of tackling new problems.
In summary, the road to intelligent systems is too elusive for us
to waste time with implausible and risky methods: we ought to follow
the steps of our brain, the best example of intelligence on Earth.
Sergio Navega.
