for me personally:
1.A framework in a fun reflective, dynamic language
(not java or c++ or something)
2.easy to add code and test it out right away (add new
logic rules, add a new module and see it at work
right away)
3.the main task of intelligence should be to
*facilitate the adding of new code
* knowing how to run and maintain itself
(not some external task like controlling robots with
no gain to the system itself)
4- have a lot of algorithms and libraries available
so i could very easily make this new module:
(that tries to learn when to save things that
are being deleted)
"see 'remove ?X'" and "interesting ?x" -> "save ?x"
and add some algorithm that learns what "interesting" is.
you need easy monitoring of the system ("remove" etc).
other people can access your saved values.. everyone's goal
is to add intelligence as a service for other people. so they
can build on it.
Another person can add a module that monitors my module
and tries to learn whether it is valuable (and might
disable it when it's not), making the system run better
5. so everyone can do their own thing, but the aim is to
make the system itself better
..
--- William Pearson <[EMAIL PROTECTED]> wrote:
> My current thinking is that it will take lots of effort by multiple
> people, to take a concept or prototype AGI and turn into something
> that is useful in the real world. And even one or two people worked on
> the correct concept for their whole lives it may not produce the full
> thing, they may hit bottle necks in their thinking or lack the proper
> expertise to build the hardware needed to make it run in anything like
> real time. Building up a community seems the only rational way
> forward.
>
> So how should we go about trying to convince each other we have
> reasonable concepts that deserve to be tried? I can't answer that
> question as I am quite bad at convincing others of the interestingness
> of my work. So I'm wondering what experiments, theories or
> demonstrations would convince you that someone else was onto
> something?
>
> For me an approach should have the following feature:
>
> 1) The theory not completely divorced from brains
>
> It doesn't have to describe everything about human brains, but you can
> see how roughly a similar sort of system to it may be running in the
> human brain and can account for things such as motivation, neural
> plasticity.
>
> 2) It takes some note of theoretical computer science
>
> So nothing that ignores limits to collecting information from the
> environment or promises unlimited bug free creation/alteration of
> programming.
>
> 3) A reason why it is different from normal computers/programs
>
> How it deals with meaning and other things. If it could explain
> conciousness in some fashion, I would have to abandon my own theories
> as well.
>
> I'm sure there are other criteria I have as well, but those three are
> the most obvious. As you can see I'm not too interested in practical
> results right at the moment. But what about everyone else?
>
> Will Pearson
>
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