Notes for the Lifebox, the Seashell, and the Soul - Rudy Rucker

Notes for The Lifebox, the Seashell, and the Soul, by Rudy Rucker
2350 Programmable clones It becomes possible to grow a clone of yourself in a tank
and program its brain with the contents of your lifebox
file, creating a person very much like yourself.
3001 The alla The age of direct matter control arrives and we can
change anything into anything. Matter is fully
programmable.
3002 Space migration People use allas to live in asteroids
3003 3ox A new technology for identically copying an existing
objects, including living beings
3150 Ooies Uvvies become internal organs, so that people are
constantly in contact. Society truly becomes a hive.
3400 Colony people Some individuals 3ox or clone hundreds of copies of
themselves, with the copies connected via ooie.
3400 Spacebug people Still more advanced bioengineering allows people to live
in the hard vacuum of outer space.
3666 Teleportation Insight into fundamental physics gives people the ability
to jump to arbitrarily distant space locations.
4050 People free to move in
higher dimensions
Travel to the other worlds beyond our space and time.
Stepping Through an Argument for the Universal Unpredictability Lemma
Let’s consider the universally computing CA Rule 110 and see what happens if we try
to carry out Wolfram’s argument sketched on NKS, p. 742, that a universal computation is
“computationally irreducible.”
Specifically, let’s look at a computation C110 such that if rowcount is an integer
measuring the number of number of rows to be computed and if input is an integer that codes
up a start pattern then C110(rowcount, input) = output, means that output is an integer coding
up the rowcount th row of a Rule 110 computation starting with the pattern coded by input.
Normally, computing C110(rowcount, input) = output takes rowcount*input + n 2
individual cell-update steps or, if you prefer, rowcount row-updates.
Now suppose we have a prediction algorithm called Predictor such that
Predictor(rowcount, input) = output maps rowcount-input pairs into output rows just like
C110 does. And suppose that Predictor computes this in some very small number of
computational steps PredictorRuntime(rowcount, input). We might imagine that for
sufficiently large rowcount and input, this runtime number might be on the order of the
logarithms of the second two arguments, that is, we might expect that
PredictorRuntime(rowcount, input) º log(rowcount)+log(input)
Wolfram’s argument suggests that we now use the universality of Rule 110 to let it
simulate the computation Predictor(rowcount, input). Simulating Predictor means that we
have a string prog coding up the program of Predictor and that we can combine prog with a
desired rowcount count and an arbitrary input to make a new argument called, say, progrowcount-input.
We feed prog-rowcount-input into C110, and by computing some as yet
unknown number of rows simulationrowcount, the computation of
C110(simulationrowcount, prog-rowcount-input) will emulate Predictor(rowcount, input) by
generating output, that is by producing the rowcount th row of Rule 110 starting with input.
p. 96