Eric B. Ramsay wrote:
If the Novamente design is able to produce an AGI with only 10-20
programmers in 3 to 10 years at a cost of under $10 million, then this
represents such a paltry expense to some companies (Google for example)
that it would seem to me that the thing to do is share the design with
them and go for it (Google could R&D this with no impact to their
shareholders even if it fails). The potential of an AGI is so enormous
that the cost (risk)/benefit ratio swamps anything Google (or others)
could possibly be working on. If the concept behind Novamente is truly
compelling enough it should be no problem to make a successful pitch.
Eric B. Ramsay
[WARNING! Controversial comments.]
When you say "If the concept behind Novamente is truly compelling
enough", this is the point at which your suggestion hits a brick wall.
What could be "compelling" about a project? (Novamente or any other).
Artificial Intelligence is not a field that rests on a firm theoretical
basis, because there is no science that says "this design should produce
an intelligent machine because intelligence is KNOWN to be x and y and
z, and this design unambiguously will produce something that satisfies x
and y and z".
Every single AGI design in existence is a Suck It And See design. We
will know if the design is correct if it is built and it works. Before
that, the best that any outside investor can do is use their gut
instinct to decide whether they think that it will work.
Now, my own argument to investors is that the only situation in which we
can do better than say "My gut instinct says that my design will work"
is when we do actually base our work on a foundation that gives
objective reasons for believing in it. And the only situation that I
know of that allows that kind of objective measure is by taking the
design of a known intelligent system (the human cognitive system) and
staying as close to it as possible. That is precisely what I am trying
to do, and I know of no other project that is trying to do that
(including the neural emulation projects like Blue Brain, which are not
pitched at the cognitive level and therefore have many handicaps).
I have other, much more compelling reasons for staying close to human
cognition (namely the complex systems problem and the problem of
guaranteeing friendliness), but this objective-validation factor is one
of the most important.
My pleas that more people do what I am doing fall on deaf ears,
unfortunately, because the AI community is heavily biassed against the
messy empiricism of psychology. Interesting situation: the personal
psychology of AI researchers may be what is keeping the field in Dead
Stop mode.
Richard Loosemore
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singularity
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