My AGI project is going to be an application of a simple AGI theory that I
have. While the database management part would not be simple to read it is
simple (and amateurish) compared to an industrial db management program. I am
not claiming that I have a solution for AGI complexity. My program is intended
to show that it is capable of making more progress than contemporary AGI
programs. It won't play Jeopardy or chess or anything like that but most of us
agree that those programs are not true AGI. My simple AGI project is intended
to show preliminary feasibility. One thing missing in most AGI programs is the
ability to build on previous learning to solve new kinds of problems. So,
while we know that a Bayesian character recognition program could be combined
with other linguistic recognition programs we don't see the character detection
program continuing on to learn to recognize spoken words, and phrases and then
use these abilities to begin to understand simple sentences. (My first simple
AGI program is not going to be able to learn to recognize handwritten
characters or spoken words but I am claiming that if it works then I would be
able to adapt it for other kinds of problems.)
So anyway, just in case someone still doesn't understand what I am saying: My
simple AGI program will not achieve true human-level intelligence, but it is
intended to demonstrate that it can build on what it has previously learned to
continue learning. So right before it is overwhelmed by complexity I am hoping
that it will go a little further than contemporary AGI programs in order to
demonstrate preliminary feasibility for a structural learning program which
unquestionably builds on previous learning. This ability to implicitly and
explicitly build on previous learning to adapt for new kinds of problems is a
fundamental ability of General Intelligence and that is what I am aiming to
create in my Simple AGI project. Or at least I am going to test my theories to
see if they are strong enough for this simple AGI project.
Jim Bromer
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AGI
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