The process of evolution is based on random mutation and natural
selection. This concept can be applied to many things, even to computer
software.
In the realm of software all software executable files take up a certain
amount of information space. If you were to randomly generate binary
code and then check it to see if it acts the way you wanted it to; it would
take an astronomical amount of time. If the result you are searching
for is compressible, then the fastest way to find it is by creating random
data sets followed by decompression. This significantly decreases the
search space, making evolution much more efficient and practical.
Figure 1 is an uncompressed bitmap image of a face. Figure 2 is a
compressed PNG image of the same face, utilizing lossless compression.
The non-compressed image is 301 kB in size. The compressed image is
221 kB in size. If you were to generate random uncompressed
bitmap image files until your result is the image in Figure 1 or
Figure 2, it would take a very long time because the search space is
301 kB in size. However, if you were to randomly generate
compressed PNG files, it would take much less time due to a smaller
search space. This only works when the result you seek is highly
compressible.
Because plants and animals are highly compressible in terms
of structure, this opens the possibility that life was created as a selfextracting,
dictionary based, structure. A self-decompressing structure
would also come before a structure made of raw uncompressed data,
due to a smaller search space.
Some evidence that human and animal development is
based on dictionary compression, is that in some tumors teeth,
bone and hair are found as well as organs. This condition is
known as teratoma. This suggests that structures in the body are
defined only once and then used many times throughout the body.
This is the way that dictionary compression algorithms work on a
computer.
meep
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