Dennis,
Over the past decades, we have heard many remarkable claims about
what this or that system can do, and the only response I can make is:
*** don’t tell us, show us ****
Is there a web site where we can log in and test these wonderful
programs with queries and problems of our own devising? If not, why not?
If and when the tool is available for download, will it be
self-contained or require other programs or utilities in order to function?
Pat
pat@xxxxxxxxx
-------- Original Message --------
Comments inline below.
Admittedly you may be skirting the self-promoting
line (we've been
educated recently about that line), but you raise
some issues that
might be interesting for our readership.
Thanks,
Leo
-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx]
On Behalf Of Dennis L.
Thomas
Sent: Sunday, September 02, 2007 2:04 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] electric sheep
Steve, Sean and Peter,
Yes, "let's get on with the
engineering." We are proponents of what
we call "theory-based semantics," meaning
that from our perspective,
the facts of the observable world are understood
according to the
theory that binds them. Knowledge = Theory +
Information, or
Knowledge = Theory + Reality. Well justified
theory, such as
scientific, axiomatic value-based understandings,
business (buy low
sell high, its better to have it sooner than later),
etc., are more
important than unfounded imagination. Theory lasts
decades,
centuries and millenniums and makes sense of our
world as we
encounter it. It understands the who, what, when,
where and how much
information of situations and circumstances. For
this reason, theory
is also predictive.
LEO: Amen, brother. This is the right perspective.
We think ontologies
are "logical theories".
Based on this, as a matter of practical knowledge
engineering, we
modeled/simulated very complex domains simply by
integrating the
knowledge content of books, policy and procedure
manuals, documents,
databases and the very knowledge in the minds of
knowledge workers
and subject experts. As a result, our systems provided
precise
answers to who, what, when, where, how much, and
how, why and what if
questions within seconds and minutes when it
previously took hours,
days, weeks and even months to arrive at the same
answers (developed
and tested through 50 projects of national
importance). http://
www.knowledgefoundations.com/pdf-files/2003KEProjects.pdf
LEO: Without yet having read this or seeming to
advocate your approach,
I must say this is a good methodology.
That 2nd generation software system had a database
backend, which
topped out at the complexity barrier. Now, our 3rd
generation
semantic knowledgebase system, called Mark 3, is
designed to be a
self-building, self-organizing and self-transcending
system that
scales to unlimited dimensions to simulate every
from of human
knowledge and to reason with that knowledge like
people. This means
that non-programming professional can build very
complex
knowledgebase products, stored at Ballard/Shannon
bit-limits, made
available through conventional network and user
systems. A small
semantic knowledgebase would have 10,000 to 50,000
concepts, a medium
knowledgebase from 50,000 to 250,000 concepts and a
large
knowledgebase into the millions of concepts.
LEO: OK, now you are weakening your hold on my
attention.
"Self-transcending" at least points you
into no-no space: the finely
delineated (by folks who work in this area) space
you enter when your
claims begin to be extravagant. When you say
"unlimited dimensions",
our hackles rise higher. It seems there must be a
learning component to
this, no? How does your system learn?
This is an enterprise tool, though we plan to offer
a FREE limited
trail copy the size of a large database for people
to play with. I
will be developing an advance notice list for anyone
who is
interested in receiving this trial version.
LEO: I would like to obtain this tool. Can you
describe some of the
foundations of this tool?
1) How do you capture and represent such wide
knowledge?
2) How do you enable complex knowledge to be
represented by
non-technical domain experts?
3) How do you scale well? I fully understand that there
are proprietary
issues here, but would like you to guide us through
potential shoals
while at the same time preserving your secrets.
Dennis
Dennis L. Thomas
Knowledge Foundations, Inc.
On Aug 31, 2007, at 7:23 AM, Barker, Sean (UK)
wrote:
Steve
In the Odyssey, Odysseus was 'agathos' (good)
exactly because he lied
and cheated in defence of his people, as was his
duty as the king. I'm
not sure that is the forum to discuss whether we
have progressed - or
whether this is an issue of philosophy or politics.
I have read your
disclaimer.
Sean Barker
Bristol,
UK
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not
represent an official company view.
> -----Original Message-----
> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
> [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx]
On Behalf Of
> Steve Newcomb
> Sent: 31 August 2007 14:31
> To: [ontolog-forum]
> Subject: Re: [ontolog-forum] electric sheep
>
>
> *** WARNING ***
>
> This mail has originated outside your
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> Keep this in mind if you answer this
message.
>
> Sean Barker wrote:
>
>> At what level of complexity do I need to
start
> concerning myself with
>> Semantics rather that just Pragmatics? At
what point would
> one say the
>> robot "understands concepts",
rather than behaves according to
>> particular pragmatics?
>
>> I should add that as we develop increasing
complex autonomous
>> systems, we need to create architectures
that provide proper
>> separation of concerns, so this is
primarily a question about
>> engineering, rather than philosophy.
>
> Autonomous military systems require significant
"separation
> of concerns", especially including
separation of the concern
> for humanity as a whole from concern for the
success of a
> narrowly-defined military mission.
>
> A robot that fetches claret is amusing, but an
autonomous
> target selector/destroyer is monstrous. If we
must have such
> things, then it might be a good idea to insist
that their
> behaviors reflect deep "concerns"
about many things other
> than their narrowly-defined missions.
>
> In a 19th-century novel that still reverberates
strongly in
> popular culture, Mary Shelley wrote about what
happens when a
> marvelous engineering task is accomplished in
the absence of
> awareness of broader issues.
>
> In a series of novels about robots, Isaac
Asimov examined the
> implications of having "Laws of
Robotics" that reflect the
> broadest concerns for the welfare of humanity.
One of the
> later novels is kind of a murder mystery; it's
all about a
> robot who is already dead when the novel
begins. By the end
> of the novel, we understand that the robot had
got himself
> into a jam in which he had no options at all,
under the
> "Laws" he was bound to obey. As a
result, he suffered from a
> kind of halting problem. It turned out to have
been neither
> murder, nor suicide, nor a system failure. In
a sense, the
> Laws of Robotics were Broken As Designed (BAD),
in that they
> did not provide a way for a robot to survive
their demands.
>
> It's so much easier to build a monster. Let's
just forget
> about those pesky philosophical questions.
Let's get on with
> the engineering!
> (;^)
>
> -- Steve
>
> Steven R. Newcomb, Consultant
> Coolheads Consulting
>
> Co-editor, Topic Maps International Standard
(ISO/IEC 13250)
> Co-editor, draft Topic Maps -- Reference Model
(ISO/IEC 13250-5)
>
> srn@xxxxxxxxxxxxx
> http://www.coolheads.com
>
> direct: +1 910 363 4032
> main: +1 910 363 4033
> fax: +1 910 454 8461
>
> 268
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> Southport,
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> Shamefully, our own generation, acting on fears
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> fraudulently-elected rogues, has allowed
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usurped by those very
> same rogues. Hail Caesar!)
>
>
>
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Managing the Complexity of Enterprise Knowledge
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