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From: PEREIRA@SRI-AI.ARPA@sri-unix.UUCP
Newsgroups: net.ai
Subject: So the language analysis problem has been solved?!?
Message-ID: <4442@sri-arpa.UUCP>
Date: Sat, 20-Aug-83 15:28:17 EDT
Article-I.D.: sri-arpa.4442
Posted: Sat Aug 20 15:28:17 1983
Date-Received: Wed, 24-Aug-83 00:58:49 EDT
Lines: 70

I will also refrain from flaming, but not from taking to task 
excessive claims.

    I'll refrain from flaming about traditional (including
    logic) grammars.  I'm tired of people insisting on a
    restricted view of language that claims that grammar rules
    are the ultimate description of syntax (semantics being
    irrelevant) and that idioms are irritating special cases.  I
    might note that we have basically solved the language
    analysis problem (using a version of Berkeley's Phrase
    Analysis that handles ambiguity) ...

I would love to test that "solution of the language analysis 
problem"... As for the author being "tired of people insisting on a 
restricted ...", he is just tired of his own straw people, because 
there doesn't seem to be anybody around anymore claiming that 
"semantics is irrelevant".  Formal grammars (logic or otherwise) are 
just a convenient mathematical technique for representing SOME 
regularities in language in a modular and testable form. OF COURSE, a 
formal grammar seen from the PROCEDURAL point of view can be replaced 
by any arbitrary "ball of string" with the same operational semantics.
What this replacement does to modularity, testability and 
reproducibility of results is sadly clear in the large amount of 
published "research" in natural language analysis which is untestable 
and irreproducible. The methodological failure of this approach 
becomes obvious if one considers the analogous proposal of replacing 
the principles and equations of some modern physical theory (general 
relativity, say) by a computer program which computes "solutions" to 
the equations for some unspecified subset of their domain, some of 
these solutions being approximate or plain wrong for some (again 
unspecified) set of cases. Even if such a program were "right" all the
time (in contradiction with all our experience so far), its sheer 
opacity would make it useless as scientific explanation.

Furthermore, when mentioning "semantics", one better say which KIND of
semantics one means. For example, grammar rules fit very well with 
various kinds of truth-theoretic and model-theoretic semantics, so the
comment above cannot be about that kind of semantics. Again, a theory 
of semantics needs to be testable and reproducible, and, I would 
claim, it only qualifies if it allows the representation of a 
potential infinity of situation patterns in a finite way.

    I don't recall a von Neumann bottleneck in AI programs, at
    least not of the kind Backus was talking about.  The main
    bottleneck seems to be of a conceptual rather than a
    hardware nature.  After all, production systems are not
    inherently bottlenecked, but nobody really knows how to make
    them run concurrently, or exactly what to do with the
    results (I have some ideas though).

The reason why nobody knows how to make production systems run 
concurrently is simply because they use a global state and side 
effects. This IS precisely the von Neumann bottleneck, as made clear 
in Backus' article, and is a conceptual limitation with hardware 
consequences rather than a purely hardware limitation. Otherwise, why 
would Backus address the problem by proposing a new LANGUAGE (fp), 
rather than a new computer architecture?  If your AI program was 
written in a language without side effects (such as PURE Prolog), the 
opportunities for parallelism would be there. This would be 
particularly welcome in natural language analysis with logic (or other
formal) grammars, because dealing with more and more complex subsets 
of language needs an increasing number of grammar rules and rules of 
inference, if the results are to be accurate and predictable.  
Analysis times, even if they are polynomial on the size of the input, 
may grow EXPONENTIALLY with the size of the grammar.

                                Fernando Pereira
                                AI Center
                                SRI International
                                pereira@sri-ai