Relay-Version: version B 2.10 5/3/83; site utzoo.UUCP
Posting-Version: version B 2.10.2 9/18/84; site warwick.UUCP
Path: utzoo!watmath!clyde!burl!ulysses!gamma!epsilon!zeta!sabre!petrus!bellcore!decvax!ucbvax!ucdavis!lll-crg!seismo!mcvax!ukc!warwick!kay
From: kay@warwick.UUCP (Kay Dekker)
Newsgroups: net.ai
Subject: Re: definition of AI
Message-ID: <2401@flame.warwick.UUCP>
Date: Sat, 4-Jan-86 10:58:56 EST
Article-I.D.: flame.2401
Posted: Sat Jan  4 10:58:56 1986
Date-Received: Mon, 6-Jan-86 03:23:53 EST
References: <33103@lanl.ARPA> <289@quest.UUCP> <2555@sunybcs.UUCP> <606@kitty.UUCP> <409@tekchips.UUCP>
Reply-To: kay@flame.UUCP (Kay Dekker)
Organization: VLSI Group, Warwick University, UK
Lines: 29
Xpath: warwick flame flame ubu

Sorry about this followup being a little delayed, but I haven't read the news
much recently, so I'm catching up over the weekend...

In article <409@tekchips.UUCP> wm@tekchips.UUCP (Wm Leler) writes:
>A side benefit of AI is that it helps us learn how intelligences
>solve these problems, and thus how natural intelligence works.
>
>Example: vision.  We do not have any algorithms for recognizing,
>say, animal faces in images, but we know it must be possible,
>because humans (even infants) can effectively recognize faces.
>Solving this problem would help us understand how human vision
>works.

I'm not sure that this reasoning is totally sound.  Sure, we may find
*solutions* to problems, but I don't see that because we produce models
that fit experimental evidence, the models will *necessarily* help us to
understand how the problems are solved "in the flesh".  Just because I have
two black boxes that produce the same combinations of outputs for the same
combinations of inputs (for example) doesn't permit me to reason "They
behave identically from the outside, therefore their interior natures are
similar."

							Kay.



-- 
This .signature void where prohibited by law
						...ukc!warwick!kay