Hi Ben,

Ahhh, all this brings back memories of the good old days
at Webmind... :)

It's just a pitty that Jeff isn't here :(


Shane, i think you and pei are  using different language to say very
similar things...
I thought that too.  But then decided that either his use of terms
was so out of line with my understanding that I would object any, or
that we really were having a deeper difference of opinion.  Either
way I decided to explore the matter futher.  (and it appears that we
do have a real disagreement which I'll get to in my reply to Pei)


It seems to me that NARS, Novamente, and any other programs that run on
Turing machine hardware (like contemporary computers) CAN be analyzed in
terms of computation theory.  The question is, the extent to which this
is a USEFUL point of view.   There may, for some programs, be
noncomputational perspectives that are more useful.
This I agree with.  Low level stuff isn't always very useful
in understanding things that are going on at higher levels.

To continue my master painting analogy:  You could look at a master
painting under a microscope for years and learn everything there
is to know about the paints used and the brush stroke technique
and so on and still have no idea what the painting was about.


But the structures and dynamics needed to make intelligence happen under
reasonable space and time resource constraints -- THESE, I believe,
necessarily involve primary theoretical constructs VERY DIFFERENT FROM
computation theory, which is a theory of generic computational processes
This I consider an open question. My belief is that many of the things
we now consider to be practical and engineering motivated do in fact
arise from foundational theory interacting with various time and space
complexity constraints. Which is, I guess, the Holy Grail of complexity
theory in a nut shell.

Even if this isn't the case (or can't be proven) I also believe that
foundational theory on the nature of intelligence and results that
follow from that will offer significant insights into the practical
construction of artificial intelligence. Hopefully work by myself
and others in my group at IDSIA should help answer some of these
important questions over the coming years!

Shane


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