My original idea about using compressed data in functions came from
numerical processes. As I said, the base n (n-ary) number system is a
major advancement from the unary stick system of counting. From that
point of view, the fact that you can use base n numbers in
computations without decompressing them into unary representations is
a major factor in their effectiveness. So maybe the development of
cross-transformation compressions is not as important as the
development of other single compression methods that would include
functions which can use the data without decompressing it.

A simple example of a cross-compression function can be found by using
Roman numerals with base n numbers in computations. Although the Roman
numeral has to be translated into base n and the reverse is also true,
from the point of view that base n is a true compression, the
translation does not require any major decompression. So that is an
interesting example of what I am talking about. From the point of view
that computational systems could be derived to take advantage of
representing some numbers over their base-n representations, then the
translation from the other kind of representation into base-n might
look like a decompression. This shows that compression is relative. So
it is really a matter of effectiveness.

I think that AGI has to be relative and that cross-indexing and
cross-generalization means that there can be an extensive number of
conditional transcendent (virtual) relations. I suspect that this kind
of system might hold a lot of opportunity for cross-transformational
functions.


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AGI
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