William,

On 6/27/08, William Pearson <[EMAIL PROTECTED]> wrote:
>
> > Unfortunately, no one here appears to be interested in understanding this
> > landscape of solving future hyper-complex problems, but instead
> apparently
> > everyone wishes to leave this work to some future AGI, that cannot
> possibly
> > be constructed in the short time frame that I have in mind. Of course,
> > future AGIs are doomed to fail at such efforts, just as people have
> failed
> > for the last million years or so.
> >
> If Humans and AGIs are doomed to fail at the task perhaps it is impossible?


The trick is to construct aids, e.g. bulldozers to move dirt, computers to
perform large numbers of high-precision calculations, etc. Difficult
problems from disparate domains have common STRUCTURES (e.g. figure 6)
composed of different elements. Computers can easily unravel these
structures much as they can (finally now at ~2GHz) easily solve the
"traveling salesman" problem for reasonable real-world-sized situations.

This is very similar to the different way that Chess masters look at a Chess
situation - as a compendium of structural elements, each with its own
strengths and weaknesses that he knows how to exploit; whereas beginning
Chess players only see pieces arrayed on a board.

Programs that work these structures aren't all that complex, though the
relationships expressed in their knowledge base may be very complex indeed.

My continuing challenge is that apparently no one prior to the Dr. Eliza
project ever looked closely at the structures of difficult problems, so this
is not taught in any school, so this is completely unknown to all audiences,
so it is hard to carry on a conversation about it, even when that
conversation would seem to be a guiding force in technological development.
Hence, people as on this forum, presume that more intelligence is needed to
solve more difficult problems, when relatively simple programs can exceed
any potential unguided intelligence, at least in some/many interesting
domains (e.g. health/medicine).

Steve Richfield



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agi
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