Dear Matthew and Henson, (01)
I mentioned Cyc because Cyc was designed to support applications for
*large systems* at gov't agencies and multibillion dollar companies.
They do applications under contract, and the only businesses that can
afford their services are big. (02)
MW
> but the kinds of big systems I am more interested in are refineries and
>aircraft
> carriers and aircraft. And I did take a particular example of what you find
> there and work it up to discover the life history and existence criteria of
> a systems component. (03)
I am *very* interested in those big systems. But I was trying to say
that a formal definition of what is a big system has *not* been useful
for the people who actually design and build big IT systems. (04)
If anyone is interested in that topic, the field called General Systems
Theory has been around for a long time. The following URLs include
(1) excerpts from the book _General System Theory_ by Ludwig von
Bertalanffy and (2) the Wikipedia article on Systems theory: (05)
http://www.panarchy.org/vonbertalanffy/systems.1968.html (06)
http://en.wikipedia.org/wiki/Systems_theory (07)
If anybody wants to know more about general systems, I recommend that
they read the literature on that subject. But I would not recommend
that the Ontology Summit devote a single session on it. (08)
HG
> Why semantic technology is needed is that
> 1. to collaborate and share engineering models without the need to have a
> domain expert present
> 2. standards for language implementations
> 3. the need for reasoning to solve engineering problems such as design
> constraint management.
> The problem is not that semantic technology is needed but where are there
> potential matches between ontology research and engineering needs. Here are
> some suggestions.
> 1. Product descriptions, e.g., parts and composite structure
> 2. domain ontologies, such a physics laws which can be included in
> engineering analysis
> 3. descriptions of engineering processes, methods, and artifacts
> 4 system of systems (09)
Those are important issues. But we've had over 20 years of such talk.
Some of it caused businesses to look at the field, to devote R & D
money to the field, and to try to implement systems that use it. But
the projects they attempted did not produce useful results. (010)
In the 1990s, I spoke with a manager of a research department at
a company that had spent a few million dollars in supporting the
Cyc project. They had access to all the Cyc software at the time,
they had sent some of their employees to attend the Cyc courses
at Austin, and they had several of their employees work on projects
that used Cyc. When I asked him about their experiences, he replied: (011)
Anonymous manager:
> Over the years, several people in our department have spent time
> working with Cyc. And a funny thing is that every one of them has
> been fired. And I don't believe that's a coincidence. (012)
I knew some of the people who worked with Cyc at that company.
They had advanced education in computer science and AI. They also
were highly motivated to find some practical applications of Cyc.
And their management gave them the resources. But they failed. (013)
Since 2004, the research funding at Cyc was sharply cut back, and
they had to shift their emphasis to making money by implementing
practical systems for clients that had jobs that needed to be done. (014)
I would like to know (1) why Cyc in its earlier form did not lead
to practical applications, (2) what is that "disconnect" between Cyc
and mainstream IT, and (3) how have they changed their methodologies
and interfaces in order to implement practical applications. (015)
As I said, one talk by somebody from Cyc would be useful. But even
more useful would be some talks by people who used Cyc or worked
with Cyc in the past and who learned (the hard way) what works
and what doesn't work when trying to build *large systems* and
to build interfaces between *large systems* and AI technology
of any kind. (016)
John (017)
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