Algorithmic principle for neural networks.

[Martin Michael Musatov]

Consider networks based on pattern recognition as having vision.
Define vision as pattern recognition. The network has the ability to
recognize relevant to by user interaction with results. Users interact
with relevant results. A high amount of relevant results in a period
of time is defined by a lower amount of interaction in equal time.
Based on the time-hierarchy all machines are programmed to accept the
following statement as the first true statement found to be always
true in all cases future and past having been checked and verified as
true to both machine and human verifiers goes good in the future
equals went well in the past after this result is recorded and checked
and verified as true the truth of this statement is found and this
statement labels eternal truth. For the purposes of producing a result
all statements are either false or true. All false statements are
always false in all cases past present or future and a true statement
is define as a statement found to be true in at least one instance and
all true statements are further defined as being either true or
eternally true. Eternally true statements are all true statements
verified as eternally true in all instances past present and future
and a true statement is simply a statement true in one instance. All
eternally true statements are true and all true statements are true
and some true statements are eternally true.