I am convinced that it would be easy to get a text-based Learning-AI
program learn to respond in fairly simple ways to simple texts.  (And
I will be in a position to try it out in the near future.) The
question is whether this kind of ability has to be at the expense of
an ability to integrate more sophisticated kinds of learning into it.

I just do not see why people have not produced solid examples of
simple learning using text-based AI unless the problem was either that
they felt they needed to impress the skeptics or they became
confounded by their own, more complicated use of language.

Simple language does not have to be at the level of a programming
language. I think that programming languages are "context free"
because even though the apparent context may seem to violate the
context of the substrings taken separately, any particular string
(that is any grammatical string) will still only generate one
particular output.

So a computer could (genuinely) learn about simple strings that might
not be context free and use them to generate different points.  As
long as this was kept relatively simple it should be completely
feasible and it might be a good starting point to examine what was
going on.  (Even though a text only AI program would not be capable of
applying its knowledge in a sophisticated way, it could still
constitute genuine learning in my opinion because it would be able to
learn new things within the domain of the text-based interactions.)

So even though my data management system is neither simple nor
sophisticated, I believe that I will be able to use it for simple but
somewhat sophisticated kind of learning which would be general within
the limits of the domain of text.

Jim Bromer


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