Thanks for giving this some thought Jim. I'm going out of town for a
few days, so don't consider silence to be a loss of interest.
One of your comments was:
"But the program has to be able to develop its
own strategies to 'evaluate' some things because that is a good
strategy for a computer program to use - in some cases. And the
usefulness of logical 'evaluation' implies that some strategy for
evaluating conceptual relationships other than simple numerical
methods would also be a good strategy to use."
---------------------
My problem with the program developing "it's own strategy to
evaluate..." is that strategy is not a strength of a child. Somehow
children acquire the ability to put 2 and 2 together, but we haven't
discovered how to get a machine to do it. What's the machine equivalent
of curiosity? I'm not convinced that we have an adequate "big" picture
to see how the pieces will eventually fit together.
The big picture looks kind of like "design and make a system that works,
even if one needs to, substitute human effort for some of the
components." Then, when the system is in place, determine how to remove
more and more of the human element. Eventually one is left with a
system that may interface with humans but only as though using them as a
resource.
By the way, I think a text only approach is a good start. I'm
interested in looking at the use of words as a way to convey "benefit."
Initial design is interesting because there are so many words and
phrases to choose from. I get it that this sounds like a chat bot, but
for me it's a way of experimenting with the idea of a benefit driven
system.
Stan
On 12/06/2015 09:17 AM, Jim Bromer wrote:
You might be able to think of ways to benefit the poor but you would
have a lot of trouble to implement them. You might be able to help a
few people but if you are like most of the rest of us that would be
it.
So you think that there are a lot of opportunities to use basic
implementation strategies to get the AI/AGI program to do something
that would be beneficial in some way? But the only problem that you
foresee is the coding? But why would that be difficult? For example, I
think that I could develop a prototype of an AGI program using text
only. If you start with something like that then it would be simple to
get started because you can find code that contains the basic forms
for text IO. The problem that I am having is that even when I strip
the plan down to what I think would be a minimum for a simple database
management program (of my own design) it still cannot be done on the
little time I have to code, and without any reason to believe that I
could get past something that would not work too well I don't have
much commitment to get going on it.
You said:
"Values (rules about values) come into play as the AGI picks the next
thing to do. But, we already know that early AGI doesn't have a
"values" structure to refer to. To program one is really not much of
an option - it is too complex to "calculate" what the value of
something is. To test the validity of my statement that it is too
complex to calculate, try it. Imagine that you are writing this into
code!"
I have tried to imagine writing that into code! (Why wouldn't I have
tried to imagine that?) But the program has to be able to develop its
own strategies to 'evaluate' some things because that is a good
strategy for a computer program to use - in some cases. And the
usefulness of logical 'evaluation' implies that some strategy for
evaluating conceptual relationships other than simple numerical
methods would also be a good strategy to use. But this would be
complicated. I think the opportunities that you mentioned would be
difficult to code as well - if you wanted to avoid getting bogged down
in code that is good for narrow-AI. The problem is that once you make
the commitment to do something that is effectively narrow-AI then
there are all sorts of enticing shortcuts that become available but
that you really need to keep to a minimum.
Using a text-only program that has to start so that it can only act on
the simple 'opportunities' (or 'low hanging fruit') of text (and
conversation of course) is where I would start. But it should be clear
that I don't want to take all the shortcuts that sort of situation
would offer. So I want my program to 'look' for opportunities on its
own so to speak. It may not be possible for a program to do that at a
very sophisticated level from our point of view, but we know that
computer programs are good at some things that we are not so good at.
So, my point of view is that the program should be able to pick up all
sorts of patterns (opportunities) that we would miss so that is where
I want to start at. Having thought about that I concluded that it
would have to be looking at the recombination of all sorts of odd
kinds of data in order to find a few combinations that might be
useful.
Jim Bromer
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AGI
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