Path: utzoo!attcan!uunet!wuarchive!psuvax1!swatsun!gessel
From: gessel@cs.swarthmore.edu (Daniel Mark Gessel)
Newsgroups: comp.ai.philosophy
Subject: Re: Reasoning Paradigms
Message-ID: <A3FRYSG@cs.swarthmore.edu>
Date: 9 Oct 90 16:29:06 GMT
References: <3586@media-lab.MEDIA.MIT.EDU> <69347@lll-winken.LLNL.GOV> <3593@media-lab.MEDIA.MIT.EDU> <69377@lll-winken.LLNL.GOV> <11@tdatirv.UUCP>
Organization: Swarthmore College, PA, USA
Lines: 26

In <11@tdatirv.UUCP> sarima@tdatirv.UUCP (Stanley Friesen) writes:

<stuff deleted>

>I suspect that this is more an indication of the relative immaturity of NN
>technology, since human brains seem to be able to deal with non-linear,
>variable-sized data structures reasonably well. [e.g. human language].
>I have no more idea than you what the solution is in NN technology, but I 
>suspect it will be found.

<more stuff deleted>

You seem to be starting from the point of view that NNs embody the way the
human brain works. Unless there have been some huge jumps in the understanding
of the human brain and it's functioning, no one knows if NNs are even close.

How the exact chemical composition of the brain affects the functioning of
the brain is unknown. Todays artificial NN cannot be assumed to capture this
accurately. To assume that future NN's will be able to is to assume that we
will be able to recreate the human brain via well defined functions (in the
Mathematical sense) which is not necessarily possible.

Dan
-- 
Internet: gessel@cs.swarthmore.edu         
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