On Wed, Aug 4, 2010 at 6:17 PM, Steve Richfield
<steve.richfi...@gmail.com>wrote:

> David,
>
> On Wed, Aug 4, 2010 at 1:45 PM, David Jones <davidher...@gmail.com> wrote:
>
>>
>> Understanding what you are trying to accomplish and how you want the
>> system to work comes first, not math.
>>
>
> It's all the same. First comes the qualitative, then comes the
> quantitative.
>
>>
>> If your neural net doesn't require training data,
>
>
> Sure it needs training data -real-world interactive sensory input training
> data, rather than static manually prepared training data.
>

You design is not described well enough or succinctly enough for me to
comment on then.


>
> I don't understand how it works or why you expect it to do what you want it
>> to do if it is "self organized". How do you tell it how to process inputs
>> correctly? What guides the processing and analysis?
>>
>
> Bingo - you have just hit on THE great challenge in AI/AGI., and the source
> of much past debate. Some believe in maximizing the information content of
> the output. Some believe in other figures of merit, e.g. success in
> interacting with a test environment, success in forming a layered structure,
> etc. This particular sub-field is still WIDE open and waiting for some good
> answers.
>
> Note that this same problem presents itself, regardless of approach, e.g.
> AGI.
>

Ah, but I think that this problem is much more solvable and better defined
with a more deliberate approach that does not depend on emergence. Emergence
is wishful thinking. I hope you do not include such wishful thinking in your
design :)

Once the AI has the tools and knowledge needed to solve a problem, which I
expect to get from computer vision, then it can reason about user stated
goals (in natural language) and we can work on how the goal pursuit part
works. Much work has already been done on planning and execution. But, all
that work was done with insufficient knowledge on narrow problems. All the
research needs to be re-evaluated and studied with sufficient knowledge
about the world. It changes everything. This is another mile marker on my
roadmap to general AI.

Dave



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agi
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