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Well, in Novamente we are not coding *specific
knowledge* that is learnable... but we are coding implicit knowledge
as to what sorts of learning processes are most useful in which specialized
subdomains...
***
I don't know, from where I sit this distinction is
artificial. Learning is generally defined as projected compression, complexity
of methods to achieve it can be sequentially increased as long as it
produces positive additional compression minus the expense,- until it matches
complexity of the inputs. In other words, optimal methods themselves should be
learned.
The Novamente design
is mathematically formulated, but not mathematically derived. That is,
individual formulas used in the system are mathematically derived, but the
system as a whole has been designed by intuition (based on integrating a lot of
different ideas from a lot of different domains) rather than by formal
derivation.
In my view, we are
nowhere near possessing the right kind of math to derive a realistic AI design
from definitions in a rigorous way.
To select formulas you must have an implicit criterion,
why not try to make it explicit? I don't believe we need complex math for AI,
complex methods can be universal, - generalization is a reduction. What we need
is a an autonomously scalable method.
Juergen Schmidhuber's
OOPS system is an attempt in this direction, but though I like Juergen's work, I
think this design is too simplistic to be a functional
AGI.
Thanks, I am looking
at it. I noticed that he starts with a known probability distribution, to me
that suggests that the problem is already solved
;-)
I don't think you're right about
the reason human learning is so slow. It is not just hardware
inefficiency,
Of course, that's only part of
it.
it is the fact that a lot of
trial-and-error-based algorithms are used in the
brain.
I call it search.
The human brain has many flaws and
is not a perfect guide for AGI, but it has far more general intelligence than
any existing computer program, and so it is certainly worth carefully studying
when designing a would-be AGI system.
How about using it?
;-)
Boris.
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