Benjamin Goertzel wrote:
Nearly any AGI component can be used within a narrow AI,
That proves my point [that AGI project can be successfully split
into smaller narrow AI subprojects], right?
Yes, but it's a largely irrelevant point. Because building a narrow-AI
system in an AGI-compatible way is HARDER than building that same
narrow-AI component in a non-AGI-compatible way.
So, given the pressures of commerce and academia, people who are
motivated to make narrow-AI for its own sake, will almost never create
narrow-AI components that are useful for AGI.
And, anyone who creates narrow-AI components with an AGI outlook,
will have a large disadvantage in the competition to create optimal
narrow-AI systems given limited time and financial resources.
Still, AGI-oriented researcher can pick appropriate narrow AI projects
in a such way that:
1) Narrow AI project will be considerably less complex than full AGI
project.
2) Narrow AI project will be useful by itself.
3) Narrow AI project will be an important building block for the full
AGI project.
Would you agree that splitting very complex and big project into
meaningful parts considerably improves chances of success?
Yes, sure ... but demanding that these meaningful parts
-- be economically viable
and/or
-- beat competing
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, somewhat-similar components in competitions
dramatically DECREASES chances of success ...
That is the problem.
An AGI may be built out of narrow-AI components, but these narrow-AI
components must be architected for AGI-integration, which is a lot of
extra work; and considered as standalone narrow-AI components, they
may not outperform other similar narrow-Ai components NOT intended
for AGI-integration...
-- Ben G
Still, it seems to me that an AGI is going to want to have a large bunch
of specialized AI modules to do things like, O, parse sounds into speech
sounds vs. other sounds, etc. I think a logician module that took a
small input and generated all plausible deductions from it to feed back
to the AGI for filtration and further processing would also be useful.
The think is, most of these narrow AIs hit a combinatorial explosion, so
they can only deal with simple and special cases...but for those simple
and special cases they are much superior to a more general mechanism.
One analog is that people use calculators, spreadsheets, etc., but the
calculators, spreadsheets, etc. don't understand the meaning of what
they're doing, just how to do it. This means that they can be a lot
simpler, faster, and more accurate than a more general intelligence that
would need to drag along lots of irrelevant details.
OTOH, it's not clear that most of these AIs haven't already been
written. It may well be that interfacing them is THE remaining problem
in that area. But you can't solve that problem until you know enough
about the interfacing rules of the AGI. (You don't want any impedance
mismatch that you can avoid.)
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