No, I don't believe that Dr. Eliza knows nothing about normal health,
or that Cyc knows nothing about illness.
-- Matt Mahoney, [EMAIL PROTECTED]
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*From:* Steve Richfield <[EMAIL PROTECTED]>
*To:* [email protected]
*Sent:* Tuesday, December 9, 2008 3:21:18 PM
*Subject:* Re: [agi] Machine Knowledge and Inverse Machine Knowledge...
Matt,
It appears that either you completely missed the point in my earlier
post, that
Knowledge + Inverse Knowledge ~= Understanding (hopefully)
There are few things in the world that are known SO well that from
direct knowledge thereof that you can directly infer all potential
modes of failure. Especially with things that have been engineered (or
divinely created), or evolved (vs accidental creations like
mountains), the failures tend to come in the FLAWS in the
understanding of their creators.
Alternatively, it is possible to encode just the flaws, which tend to
spread via cause and effect chains and easily step out of the apparent
structure. A really good example is where a designer with a particular
misunderstanding of something produces a design that is prone to
certain sorts of failures in many subsystems. Of course, these
failures are the next step in the cause and effect chain that started
with his flawed education and have nothing at all to do with the
interrelationships of the systems that are failing.
Continuing...
On 12/9/08, *Matt Mahoney* <[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]>> wrote:
Steve, the difference between Cyc and Dr. Eliza is that Cyc has
much more knowledge. Cyc has millions of rules. The OpenCyc
download is hundreds of MB compressed. Several months ago you
posted the database file for Dr. Eliza. I recall it was a few
hundred rules and I think under 1 MB.
You have inadvertently made my point, that in areas of "inverse
knowledge" that OpenCyc with its hundreds of MBs of data still falls
short of Dr. Eliza with <<1% of that knowledge. Similarly, Dr. Eliza's
structure would prohibit it from being able to answer even simple
questions regardless of the size of its KB. This is because OpenCyc is
generally concerned with how things work, rather than how they fail,
while Dr. Eliza comes at this from the other end.
Both of these databases are far too small for AGI because neither
has solved the learning problem.
... Which was exactly my point when I referenced the quadrillion
dollars you mentioned. If you want to be able to do interesting things
for only ~$1M or so, no problem IF you stick to an appropriate corner
of the knowledge (as Dr. Eliza does). However, if come out of the
corners, then be prepared to throw your $1Q at it.
Note here that I am NOT disputing your ~$1Q, but rather I am using it
to show that the approach is inefficient, especially if some REALLY
valuable parts of what it might bring, namely, the solutions to many
of the most difficult problems, can come pretty cheaply, ESPECIALLY if
you get your proposal working..
Are we on the same page now?
Steve Richfield
------------------------------------------------------------------------
*From:* Steve Richfield <[EMAIL PROTECTED]
<mailto:[EMAIL PROTECTED]>>
*To:* [email protected] <mailto:[email protected]>
*Sent:* Tuesday, December 9, 2008 3:06:08 AM
*Subject:* [agi] Machine Knowledge and Inverse Machine Knowledge...
Larry Lefkowitz, Stephen Reed, et al,
First, Thanks Steve for your pointer to Larry Lefkowitz, and
thanks Larry for so much time and effort in trying to relate our
two approaches..
After discussions with Larry Lefkowitz of Cycorp, I have had a bit
of an epiphany regarding machine knowledge that I would like to
share for all to comment on...
First, it wasn't as though there were points of incompatibility
between Cycorp's idea of machine knowledge and that used in
DrEliza.com, but rather, there were no apparent points of
connection. How could two related things be so completely
different, especially when both are driven by the real world?
Then it struck me. Cycorp and others here on this forum seek to
represent the structures of real world domains in a machine,
whereas Dr. Eliza seeks only to represent the structure of the
malfunctions within structures, while making no attempt whatever
to represent the structures in which those malfunctions occur, as
though those malfunctions have their very own structure, as they
truly do. This seems a bit like simulating the "holes" in a
semiconductor.
OF COURSE there were no points of connection.
Larry pointed out the limitations in my approach - which I already
knew, namely, Dr. Eliza will NEVER EVER understand normal
operation when all it has to go on are *_AB_*normalities.
Similarly, I pointed out that Cycorp's approach had the inverse
problem, in that it would probably take the quadrillion dollars
that Matt Mahoney keeps talking about to ever understand
malfunctions starting from the wrong side (as seen from Dr.
Eliza's viewpoint) of things.
In short, I see both of these as being quite valid but completely
incompatible approaches, that accomplish very different things via
very different methods. Each could move toward the other's
capabilities given infinite resources, but only a madman (like
Matt Mahoney?) would ever throw money at such folly.
Back to my reason for contacting Cycorp - to see if some sort of
web standard to represent metadata could be hammered out. Neither
Larry nor I could see how Dr. Eliza's approach could be adapted to
Cycorp, and further, this is aside from Cycorp's present
interests. Hence, I am on my own here.
Hence, it is my present viewpoint that I should proceed with my
present standard to accompany the only semi-commercial program
that models *_malfunctions_* rather than the real world, somewhat
akin to the original Eliza program. However, I should prominently
label the standard and appropriate fields therein appropriately so
that there is no future confusion between machine knowledge and
Dr. Eliza's sort of inverse machine knowledge.
Any thoughts?
Steve Richfield
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