From newshub.ccs.yorku.ca!ists!helios.physics.utoronto.ca!news-server.csri.toronto.edu!rpi!usc!cs.utexas.edu!uunet!tdatirv!sarima Wed Dec 18 16:02:29 EST 1991
Article 2220 of comp.ai.philosophy:
Path: newshub.ccs.yorku.ca!ists!helios.physics.utoronto.ca!news-server.csri.toronto.edu!rpi!usc!cs.utexas.edu!uunet!tdatirv!sarima
>From: sarima@tdatirv.UUCP (Stanley Friesen)
Newsgroups: comp.ai.philosophy
Subject: Re: From neurons to computation: how?
Message-ID: <332@tdatirv.UUCP>
Date: 17 Dec 91 19:50:59 GMT
References: <40640@dime.cs.umass.edu> <12707@pitt.UUCP> <40684@dime.cs.umass.edu> <12721@pitt.UUCP>
Reply-To: sarima@tdatirv.UUCP (Stanley Friesen)
Organization: Teradata Corp., Irvine
Lines: 18

In article <12721@pitt.UUCP> geb@dsl.pitt.edu (gordon e. banks) writes:
|>>And I mean computable in the sense that physical computers as we build them
|>>today could compute the same data transform as any given neuron (including
|>>the temporal variability we calling learning).
|
|OK, I agree with you on this.  We aren't very close with today's technology.
|We can attack some simple pioneering problems, but we're a long ways
|from being able to link billions of neural processors at this point.

Certainly.  No disagreement here.

That is essentially what I meant by the 'shear, overwhelming complexity"
remark.  Connecting billions of nodes into a giant network to test whole-
brain theories is simply beyond current technology.
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uunet!tdatirv!sarima				(Stanley Friesen)



