After I wrote that message I realized that I had tried to start
discussions about an artificial language that could be used to shape a
general AI program before. Many of these discussions were side tracked
when people started talking about Esperanto or about lambda calculus
based artificial languages and stuff like that. That is not what I am
thinking of.

The artificial language could be used with video or audio or other
kinds of IO environments, but I would use it along side of an attempt
to get the AI program to learn to use a natural language. One of the
dreams of old AI was that if you started instructing the program to
learn using the artificialities of some kind of language it would
eventually have enough information for genuine learning to emerge.
This never really worked. Why not? Partly because computers were not
powerful enough in the old days and, in my opinion, AI researchers had
not appreciated the necessity of sophisticated data integration
methods for some reason. (Old computer systems might one day be shown
to have been potentially powerful enough to run some future program
but they were not powerful enough to entertain the trial and error
process that would have been required using experimental programs of
the day. For example, with better conceptual integration methods a
future efficient AI program might be used on an old computer system
just to show that it could be run on it.)

So the artificial referent language would not be a complete language
(of communication) like Esperanto wants to be. And it would not be a
logically sound language like lambda calculus wants to be. It could be
used to establish referents from the IO data environment. It would
need to be capable of denoting a distinction between how those data
objects can be used. For example in natural language there is an
important distinction between syntax and semantics. So if I used this
referent language with a natural language IO then one of the
artificialities would be to distinguish syntactic relations from
semantic relations. On the other hand, this distinction is not always
necessary, desired or clear cut. To explain this, many (or maybe most)
(what I think are) desirable syntactic relations are based on some
semantic conditions. But then again there is no reason not to design
the artificial language to be able to represent relations that are
mixes of semantics and syntax.

As I see it, the main problem with language based AI has been the lack
of a really good conceptual integration solution.

One of the reasons I write to groups like this is that I want to get
some ideas about how an idea might work. But when I wrote about an
artificial para-language before I wasn't really sure it I even wanted
to use it. I finally have come to the conclusion that it makes a lot
of sense. I can use it to speed up tests about my AI/AGI theories but
then I could also test those theories with more relaxed instructions.
So the artificial para-referent language would not a all encompassing
language of communication, it would not be a logically sound language
other than to denote semantic and syntactic references and relations
based on mixes of semantic and syntactic references. It could also
denote relations that I think would be important to a text-based
AI/AGI program. Because the logic of the method would not be tight and
a contradicting case would not (always) lead to an artificially
reported error, the AI methods would have to do some learning for
itself. So the para-referent language would not sidetrack the whole
effort because if the AI methods have to have the potential to exhibit
some genuine learning. And because it is not an all encompassing
language of communication it could be used to test the 'emergence' of
insight that could arise if enough preparatory work had been done,
even if I haven't figured out how that could be done without the
artificial referent language. The benefit is that I could use it to
test and develop my AI theories. I am really excited by this idea this
time.
Jim Bromer


On Sat, Nov 7, 2015 at 10:22 PM, Jim Bromer <[email protected]> wrote:
> I was just working on my latest p=np? idea and I hit up against method
> that is either in np or is otherwise extremely inefficient. So I have
> to come to the conclusion that the human mind is not capable of SAT in
> p.
>
> So then how do we figure how to deal with so many complicated
> situations? Of course I still don't know because so many situations
> seem similar to a SAT problem. The mind must be able to detect many
> different things that are going on at once or which might be useful to
> recall from memory to deal with a situation. But still, there is
> nothing in my own introspective analysis of my thinking which looks
> anything like a p=np process.
>
> So what is wrong with AI? One thing that AI has been consistently
> lacking is the ability to learn through conversation. My feeling is
> that this is not just a problem with communication but a learning
> problem as well. In other words AI is not able to truly learn except
> in a few special cases. Most of those special cases are examples of
> narrow AI but there are others where the learning that takes place
> isn't necessarily like other narrow AI but where the domain of
> learning is so restricted that it is narrow in the sense that the
> applicability of the method is limited.
>
> Then I started thinking of an artificial language which can refer to
> situations or objects in the IO data environment and which can be used
> to instruct a program as it is running. I think this is an unusual
> idea.
>
> One of the characteristics about programming methods that seem to
> catch on with programmers is that they can be used in a very simple
> manner and in more complicated programming. I think an artificial
> language which could be used to instruct a computer to notice objects
> in the IO data environment and which could also be used to refine
> those instructions using this artificial language with the references
> that it had previously established has a lot of potential. And it can
> help us become more clear about what is needed to make better AGI
> programs.
> Jim Bromer


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AGI
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