Path: utzoo!attcan!uunet!tdatirv!swf
From: swf@tdatirv.UUCP (swf)
Newsgroups: comp.ai
Subject: Re: Hayes vs. Searle
Message-ID: <114@tdatirv.UUCP>
Date: 10 Jun 90 15:30:56 GMT
References: <4550@castle.ed.ac.uk> <3204@se-sd.SanDiego.NCR.COM> <1990Jun9.154316.29020@ux1.cso.uiuc.edu>
Reply-To: swf@tdatirv.UUCP ()
Organization: Teradata Corp., Irvine
Lines: 39

In article <1990Jun9.154316.29020@ux1.cso.uiuc.edu> (Ward Page) writes:
>
>You're right.  I believe that this is at the heart of his argument.  There
>is an interesting thought experiment in Moravecs 'Mind Children' that
>talks about this.  The argument goes this way: If an artificial neuron were
>developed that exactly mimics (functionally) a brain cell and you replaced
>one neuron in the brain with this artificial neuron, would you still be
>capable of thought?  If the answer is yes, how many neurons could you replace
>before you are incapable of thought?  At the heart of this thought experiment
>is the ability to exactly mimic a neuron.  Searle would have to reject this
>to refute the argument (assuming the artificial neuron is made of different
>stuff than the real neuron).
>
This is very interesting, given that most current research in neural
networks is being done using simulations on serial computers, rather
than actual neural net hardware.  I think I can now give a skeleton
outline of the "rule book" used in the Chinese Room.

There are two subsets to the rule-set.  The first is a functional
description of the neural network complex that is formed by the
linguistic centers of the human brain. (Sufficient to either simulate
or construct a replica of it)  The second rule-set is a description of
the particular connection weights by which the linguistic NN is
specialized for Chinese, rather than some other language.  Now simulate
the result on a sufficiently powerful computer, using a standard NN
simulation (or in a Chinese Room with enough workers).  The result:
	A Chinese Room that processes Chinese *exactly* the same way
	as humans do, but in silicon rather than carbon!!

Now, either the CR "understands" Chinese, or *no* human "understands"
Chinese, since both are using the same mechanism!!

Now admittedly, this is beyond current technology, but it is certainly
theoretically plausible, given current directions in AI research.  Perhaps
this is the "intuitive" counter-argument that was previously asked for?

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uunet!tdatirv!swf				(Stanley Friesen)
swf@tdatirv.UUCP