I watched the video on Binons but not the one on Hierarchies. I have been
at this for longer than I care to admit so I feel that I have seen things
like this before. I am looking forward to watching the video on
Hierarchies. My imagining of what I might be able to effectively use as a
kind of conceptual mathematics is not going to be answered by a nodal
network kind of thing - even though it would probably be accurately
described as a kind of nodal network. Does that make sense? If someone
talked about a nodal network I would think of something that was similar to
a neural network or a conceptual network. But, the thing is, that both
these networks are going to use conventional mathematical methods to
represent the weights of the system (or the discrete decision methods of
the system.) Now, even if I was able to successfully develop my idea of a
different kind of mathematics it still could be analyzed using traditional
or conventional computational methods. So it would probably be describable
using nodal networks along with conventional mathematics. But the point is
that maybe there is some kind of non-conventional mathematics that could be
useful and especially efficient in a specialized AI program, just because
the program is specialized and does not need to apply the broad range of
utilizations that conventional mathematics can reach.
I am interested in the video of the Hierarchies and I will watch it tonight.
Jim Bromer


On Tue, Jun 11, 2019 at 10:05 PM Brett N Martensen <br...@adaptroninc.com>
wrote:

> Hi Jim,  I've been following this discussion with interest. Good stuff.
> If you are looking for a way of representing those millions of bits and
> only use a small part of it at a time and build it hierarchically may I
> suggest you look into binons.  In the presentations on binons and the
> presentation on hierarchies (slide 13) it shows how to combine many
> independent properties/features using binary nodes.  The website is
> www.adaptroninc.com   Cheers, Brett
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