The Positional Notation System of numbers, like Binary and Decimal numbers,
is a representational system which is a compression of the most natural way
to represent a count, the unary system where a single mark is used to
denote each individual item that is being counted. This Positional Notation
system has a complexity value of a lossless exponential increase in
efficiency for each digit of the binary representation.  The method of
addition, when converted into a true Boolean Form almost certainly has an
exponential increase in complexity for both the number of bits of the
addends and the number of addends.  Multiplication represents an
exponential increase in efficiency over the method of addition for that
special class of addends which represents one multiplicand being added over
and over again by the number of times represented by the value of the other
multiplicand.  These standard algorithms of addition and multiplication are
both lossless. Algebra, which might represent one of the earliest
programmable systems imagined, is so effective just because you can use
addition, subtraction, multiplication and division of the coefficients of
the literal variables of an algebraic statement.

So the binary system, addition and multiplication are really the engines of
computation.  I believe that the reason these methods are so powerful is
because they can use extremely efficient compressed representations of
numbers without needing to decompress them everytime they are used.  I have
tried to come up with some kind of terminology to represent this and I have
suggested that addition and multiplication are procedural compression
methods and transformational compression methods because they are able to
use compressed data in its compressed form.  Perhaps I should say that they
are procedural methods that can act on a kind of compressed data.

The reason why I mention this is because it may help to better define what
is needed to make AGI feasible.  I believe that many schemes which have
used efficient numerical methods on objects of AGI have failed because they
really did not adequately model the kinds of things that need to be modeled
in an AGI program.  So my thesis is that if we cannot just throw numerical
methods at AGI programs and make them work, then maybe we should take a
look at the reason why these methods are so powerful.  And they are
powerful.

Jim Bromer



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