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From: loren@tristan.llnl.gov (Loren Petrich)
Newsgroups: comp.ai
Subject: Re: What Has Traditional AI Accomplished?
Message-ID: <69460@lll-winken.LLNL.GOV>
Date: 8 Oct 90 22:45:36 GMT
References: <69367@lll-winken.LLNL.GOV> <1990Oct7.003647.1666@watdragon.waterloo.edu>
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In article <1990Oct7.003647.1666@watdragon.waterloo.edu> cpshelley@violet.uwaterloo.ca (cameron shelley) writes:
>In article <69367@lll-winken.LLNL.GOV> loren@tristan.llnl.gov (Loren Petrich) writes:
>>
>>	I know that this question may well start a big flame war, but
>>I would like an idea of exactly what traditional AI has accomplished.
>>
>  I won't try to speak for all of AI, but I would like to through in
>my two cents worth here.  Firstly, an *exact* rundown of what AI has
>been up to since its inception would take volumes.  Secondly, I'm not
>quite sure what you're refering to with "traditional" AI...

	I guess I should have been more explicit about it.

	I meant AI with inference rules stated explicitly, rather than
AI with inference rules that are "learned" by the system. Most of
"traditional AI" has not been able to "learn", and perhaps that is my
whole problem with the field -- how to derive whatever inference rules
are necessary.

>>	Is it fair to say that computer algebra is the only
>>application of traditional AI that has had any widespread use?
>>
>	[a whole list of applications, include game programs]

	I concede that certain computer game programs constitute
widespread applications of AI. Some of the other examples do not seem
terribly well-known. I was talking from my experience, which is that
there has been an abundance of research on AI, but a shortage of
(1) relatively accessible formulations and (2) practical applications.
I guess I was thinking of some AI system with (1) performance, (2)
accessibility, and (3) workability outside of an AI-lab environment as
the computer algebra systems that have been developed -- Macsyma,
Mathematica, Maple, etc.

	As a happy user of computer algebra systems, I have not needed
to learn the underlying principles of the operation of
computer-algebra systems, however desirable it may be to do so. I have
also been able to do just about everything with them by myself, though
with the help of some manuals. I have not needed the continual
assistance of the writers of these packages in order to use them. I
have also been able to do a remarkable variety of things with the
computer-algebra packages I have used.

	My basic question was, has there been any other AI application
with that kind of success?

>>	I am not trying to pick on the AI field, but I really think
>>that it has not come very far over the decades that it has been in
>>existence.
>>
>  Well, thinking of the start of computational linguistics, which is
>the area I'm most familiar with, AI started out as statistical analyses
>of text (frequency of use of certain constructions/lexical items) to 
>try and resolve authorship disputes.  Today the structural analysis
>of text is reasonably sophisticated, allowing the formal study of
>such slippery things as style, or even good machine translation which
>proved to be a terrible flop when first attempted in the 50's.

	That's certainly fine, but has there been much outside of the
AI lab? Are there many language-translator programs on the market?

>  I think that AI has come quite far over its current life.  The reason
>that it continues to disappoint some is that as more advances are
>made, the number of new problems to be solved only increases, and the
>true difficulty of answering old questions is only then truly
>appreciated.  AI is by definition (or lack of definition :) an open
>area, and so it constantly expands as it's moved into.  If you're
>expecting some sudden, radical overhaul in your life, you will likely
>be disappointed. :(

	I was not insisting on any such thing. As I commented earlier,
I was wondering if there was any other success comparable to computer
algebra.


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