We're not the only ones

Bruce Nevin (Mon 93081 09:54:23 EDT)

Here we see computational neurobiologists confronting technological
fashion with a plea for real acquaintance with real organisms.

(I'm still not back on the net, but listening in periodically.)

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To: machine-learning@BBN.COM, neural-people@BBN.COM
Subject: [jbower@smaug.bbb.caltech.edu: ]
From: "Albert G. Boulanger" <aboulanger@ldgo.columbia.edu>
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Date: Thu, 28 Jul 94 11:42:12 PDT
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To: Connectionists@cs.cmu.edu
From: jbower@smaug.bbb.caltech.edu

I remember a conversation with Chris Langton, wondering what the
next hot topic will be ...
the time is ripe for the birth of a new field, which I call simply "Brain
Building". I'm sticking my neck out here, but I feel fairly confident this
will happen. I'm predicting that the field of ALife will give birth to this
new field. I'm curious to see how other people feel about this prediction.

Low power analog vlsi chips already exist that can analyze visual and auditory
sensory inputs and cortical circuit chips are being developed by Rodney Douglas
and Misha Mahowald; the principles of sensorimotor integration as
studied by Dana Ballard and Richard Andersen are at the focus of
the theoretical breakthroughs that will be needed to achieve the
goal of autonomy in the real world by the next century.

So it is time for the birth of a new neural networks/AI/AL field, must be
funding is getting tight. This time, is it at all possible to avoid the
hype inherent in words like "Brain Building", with objectives like
"building living creatures". "Neuromorphic Engineering" is bad enough.
After 10 years, I continue to fail to see any intellectually justifiable
reason for such descriptions. It seems to me we have not yet completely
acheived the prediction of the original neural networks DARPA report that
the brain of a bee would be understood within 5 years. That was 6 years ago
and it seems to me that the bee still withstands our best efforts. Now we
are being launched in the direction of creating autonomous life based on
sensory/motor processing in primates "by the next century". Maybe it will
be easier to understand the brain of a primate than a bee, but I doubt it.
Or maybe it is not necessary to understand the device being emulated before
building it.

Last week the third annual Computational Neuroscience Meeting was held in
Monterey, California. The entire meeting was devoted to experimental and
theoretical studies of real biological "neural computation". That is,
presentations at the meeting concerned the detailed structure and possible
computational significance of real "brains". The meeting had 250 attendees
from throughout the world and represented many if not most of the leading
institutions and laboratories involved in studying real neural computation.
Despite this fact, and despite repeated invitations via, among others, the
connectionist mailing list, almost no one from the neural networks
community attended. This mirrors what appears to be the remarkably common
perception of neurobiologists who attend meetings like NIPS, INNS, etc.
that there is little real interest, or understanding, of neurobiology in
the neural networks community.

That said, I would like to issue an open invitation to those of you on the
connectionist mailing list who would actually like to know more about the
neural systems you propose to morph. The organizers of the CNS meetings
have established a new mailing list for those specifically interested in
computational neurobiology. That is, for those interested in trying to
figure out how real brains compute. It will be managed in much the same
fashion as the
connectionist mailing list with Dave Beeman in Boulder, Colorado as the
first moderator. One of the initial postings will be a synopsis of the
"hot research topics" in computational neuroscience that came out of the
post meeting workshops (building life was not one of them).

We anticipate and encourage cross-fertilization between the two mailing
groups. However, it is hard to avoid the interpretation that, at least at
this point, what is interesting to computational neurobiologists is
apparently not of much interest to those working in neural networks and
vice versa. At the same time, it is also the case that there are many
fewer neurobiologists justifying their research with reference to neural
networks than there are engineers claiming to be brain builders. Thus, my
periodic postings.

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