Yeah of course we are very familiar with the concept of a seed AI from
online discussions back to 2001 or so, on the AGI and SL4 email lists
etc. etc.

The concept is the right one... but bear in mind that a biological
seed itself is a very complex system... in my view we are now building
the seed (the current version of OpenCog) and it is simple compared to
what it will grow into, but still complex for our paltry human minds
to grapple with ...

The main obstacle we face now, apart from numerous annoying and
complex issues of "plumbing" (software scalability, documentation,
interfacing with other software systems) and funding developer time,
is making backward chaining inference algorithmically scalable via
solving the adaptive pruning problem (letting the system identify what
patterns have characterized successful inferences in the past, and use
these patterns to guide its future inferences, using the inference
engine itself to recursively assist with the pattern-identification
process).   We are having a small workshop here next week in HK to
focus on this problem...

ben

On Sun, May 7, 2017 at 10:38 PM, Alex <[email protected]> wrote:
> In the depths of the Web I have found such notions as "seed AI" and
> "bootstraping self-improving AI" -
> http://www.sciencedirect.com/science/article/pii/S1877050914015403 this is
> exactly the same idea what I am trying to pursue, but - contrary to others -
> I am trying to do this with OpenCog.
>
> BTW, there is great BICA society and Elsevier issues quite prominent
> (indexed) journal Biologically Inspired Cognitive Architectures. I was not
> aware of this activity and now I am happy to this in action.
>
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-- 
Ben Goertzel, PhD
http://goertzel.org

"I am God! I am nothing, I'm play, I am freedom, I am life. I am the
boundary, I am the peak." -- Alexander Scriabin

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