Newsgroups: comp.ai
Path: utzoo!utgpu!watserv1!maytag!watdragon!violet!cpshelley
From: cpshelley@violet.uwaterloo.ca (cameron shelley)
Subject: Re: What Has Traditional AI Accomplished?
Message-ID: <1990Oct12.192833.7783@watdragon.waterloo.edu>
Sender: daemon@watdragon.waterloo.edu (Owner of Many System Processes)
Organization: University of Waterloo
References: <69367@lll-winken.LLNL.GOV> <1990Oct9.184502.106@watdragon.waterloo.edu> <1712@oravax.UUCP>
Date: Fri, 12 Oct 90 19:28:33 GMT
Lines: 25

In article <1712@oravax.UUCP> daryl@oravax.UUCP (Steven Daryl McCullough) writes:
>The way I understand it, though, language translation for things like
>weather reports is being dropped in favor of language generation. In
>language generation, the input is data about the weather (or whatever)
>in the form of machine-readable charts and so forth, and the output is
>a natural language document. By replacing the grammar and semantic
>database, one can generate English, French, Innuit, or whatever. This
>is much more successful than language translation, since translation
>requires a high degree of understanding of the two languages.
>
>Daryl McCullough

This is not true, at least as far as I know.  All forms of machine language
'use' are not very well funded but I don't think generation has really
begun replacing translation, so much as complementing it.  Translation
has been focusing more on the harder task of  dealing with real texts in 
identifiable genres, while generation could be used as you describe, I
just don't know of any examples.  Perhaps it is different in the 'real
world'.

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