[comp.ai.neural-nets] Paradigm Shift Response

worden@ut-emx.UUCP (worden) (08/11/89)

It seems to me that most NN folks are doing their honest best
with what little we know now.  (And a thousand curses on those
few but vociferous money-sniffer dilettantes!!)

As I understand it, our sensory and motor systems are highly
structured, from the peripheral nerves to at least several
cortical layer depths.  Beyond that, through the association
areas and into the deeper structures of the limbic system,
no one really knows what the h--l is going on.

So, it doesn't surprise me that most NN folks work with the
structured networks.  After all, there can thereby be hope
that one's model will be biologically verified.  And, such
work is not without merit; there remains a great deal to be
understood, even in the sensory/motor systems about which
we know the most.

My personal preference, however, is for the random type of
networks.  Not as sensory/motor systems, but as possible
models of the deeper systems.  I have a nice micrograph,
from the old 1979 Scientific American special issue on the
brain, that shows a tangled mass of stained brain tissue.
Apparent randomness, at least, does seem to coexist with
structure inside our skulls!

What I would really like to see, though, if it is not too
premature, is collaboration between you majority structure
enthusiasts and us minority randomness aficionados, along
with some A.I. folks, to seriously attempt to build a
"complete" system.  My thought would be to use structured
NN's for sensor input/processing and low-level learning,
feeding into random NN's for multisensor fusion and mid-
level learning, feeding into an A.I. subsystem for high-
level learning and decision-making, feeding into random
NN's for multi-effector fission, feeding into structured
NN's for pre-effector conditioning and effector output.

By the way, if any of you have any references to recent
collaborative work between structured NN and A.I. folks,
I would be very interested in getting them.  Please email
the info to me (or to this newsgroup).

Finally, I believe that all of us are lacking critical,
fundamental knowlege of some kind about how our brains
work and that it is this deficiency that now prevents us
from building systems that behave the way we would really
like (i.e., in a "truly intelligent" fashion).  I just
cannot buy the arguments that greater size or greater
speed or greater complexity or even greater biological
realism is the "answer".  I do believe that part of the
answer lies in building hybrid systems, but I think that
there is a deeper mystery.  Perhaps some cellular function
that has yet to be observed and/or understood.  Perhaps
an interaction between neurons and glia, as suggested by
that recent Scientific American article.  Perhaps some
phenomenon that we don't even suspect at this point...

- Sue Worden
  Electrical and Computer Engineering
  University of Texas at Austin

jk3k+@andrew.cmu.edu (Joe Keane) (08/13/89)

In article <16946@ut-emx.UUCP> worden@ut-emx.UUCP (worden) writes:
>As I understand it, our sensory and motor systems are highly
>structured, from the peripheral nerves to at least several
>cortical layer depths.  Beyond that, through the association
>areas and into the deeper structures of the limbic system,
>no one really knows what the h--l is going on.

Not yet at least.

>Apparent randomness, at least, does seem to coexist with
>structure inside our skulls!

If you looked at a microprocessor chip you might say the same thing.  I don't
think biological neural nets are as structured as silicon chips, or we might be
looking for `grandmother cells'.  But i don't think they're completely random
either.  It's up to NN people and neurobiologists to figure out which
structures are useful.