Ed Porter wrote:
WHAT ARE THE MISSING CONCEPTUAL PIECES IN AGI?
One that appears to me to be missing, or at least not emphasized, is
that general intelligence is inefficient compared to specialized
techniques. In any particular sub-domain specialized intelligence will
be able to employ better heuristics and a more appropriate and more
efficient methodology. One that might well not work very well in a more
general case.
As a result a good AGI will have a rather large collection of
specialized AIs that are a part of it's toolbox. When it encounters a
new environment or problem, one of the things it will be doing, as it
solves the problem of how to deal with this new problem, is build a
specialized AI to handle dealing with that problem. In normal
circumstances, what the AGI will do is classify the kind of problem it's
dealing with, and hand it off to a more specialized AI. (And monitor
the process, to make sure that the problem continues to fit the mold.)
My expectation is that AGIs (without their toolbox) will be quite slow
and inefficient with dealing with any particular situation. OTOH,
*with* their toolbox they should be able to evolve to be more efficient
than humans. (Note that efficient is relative to the hardware that
they're running on. And each "solution" is likely to consider that a
part of it's presumptions is that the hardware remains unchanged.
Adapting an existing solution to new hardware is likely to be a hard
problem. On a level of re-writing a program from Java into Fortran.
It is my expectation that this approach will be necessary across a wide
gamut of AGI designs, and that unitary minds will be scarce to
non-existent. Certainly people work this way. Consider the process of
learning a new musical instrument, or of learning to read music. You
build a specialized module in your mind to handle the problems involved.
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agi
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