Thanks Jim. I appreciate your feedback. Not everyone here is trying to code AI, 
or AGI. My interest lies broader in terms of testing theory for stochastic, CAS 
at the highest level of abstraction. It's a truth that my theory and 
hypergraphs seem to have met up, but that should be the case if one was trying 
to consistently practice good science.

There's so much interest currently in state-driven systems, the notion being 
they would be best suitable for AGI, and they probably would be. However, a 
perfect-state "machine" would only form a part of the enabling architecture for 
AGI.

With regards issues of supercomputing, I still like to defer to the hard 
lessons learned from the Japanese GRAPE system.

There was a time, when pseudo code was all the rage for MMI solutions. 😉

________________________________
From: Jim Bromer <[email protected]>
Sent: Saturday, 23 October 2021 17:20
To: AGI <[email protected]>
Subject: Re: [agi] Re: Ideas Have to Act on Other Kinds of Ideas

Nanograte: I do not want to be rude, but if you have interpretable AI networks 
figured out then just apply those rules to an actual AI program.  I cannot 
understand what precisely you are saying, but the graph or model is never 
mature (in a constrained sense of graph theory) if you introduce hypergraphs, 
which are necessary.  It is not only Godelean self-referential step-state 
contradictions, but there are an extensive range of automated referential 
logical issues (like circular reasoning) that would create complications that 
need to be managed.  I have circular reasoning "all figured out" but there are 
other more subtle problems that cannot be foreseen by the programmer at a 
purely abstract level. I am not claiming to be an expert (at graph theory or 
hypergraphs and so on) but I believe that I have thought about these issues at 
a more intuitive level.
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