[ExI] Vermis ex machina
avant at sollegro.com
Sun Mar 1 00:20:20 UTC 2015
This is good news for uploaders:
Apparently the Open Worm Project has managed to successfully simulate
approximately 1/3 of C. elegans' neuronal network and uploaded it into
a robot body that displays "wormy" behavior.
Here is an excerpt:
"He said the scientific road map is to model the worm completely,
equipping it with the same physics right down to the cells in all the
While the C. elegans nematode was chosen because of the simplicity of
its biological structure, the complexity of the experiment has been
such that the team has had to narrow down the project to just a third
of the worm's neurons, restricting it to those parts of the worm's
make-up that would display behavior.
The digital version of the worm will be released on the web in June
this year, allowing anyone with an interest to tinker with the project.
Larson said the open source and collaborative nature of the project
has been key to its success, allowing it to make fast progress over
the four years of its existence."
So this gave me an idea on how to estimate the Kolmogorov complexity
of the human brain. 1st you simulate all of C. elegans 302 neurons and
their 6393 synapses. (My numbers are from
http://www.wormatlas.org/neuronalwiring.html) Once you get a the open
worm simulation up and running with sufficiently accurate worm-like
behavior, you take all of the computer code involved as a measurement
of the byte size of the C. elegans simulation. I tried looking around
their website for how big the simulation was but couldn't find it. Not
that it matters right now since they say they are only a third done
anyway. So lets just call it "B(w)" as in "byte size of worm" for now.
Now to determine the Kolmogorov complexity one can compress the open
worm software down using some compression scheme such as zip or rar
and then measure the size of the compressed files. This will give you
the Kolmogorov complexity of the simulated worm which we can designate
Now the connectivity map of worm's nervous system can be represented
by a graph 302 vertices and 6393 edges. One can represent such a graph
as a 302 X 302 matrix of ones and zeroes called an adjacency matrix.
The adjacency matrix will be 91204 bits in size. 12786 of those bits
would be 1's and the remaining 78418 bits would be 0's.
A human brain contains 86 billion neurons, so its adjacency matrix
would be 7.396 x 10^21 bits in size or roughly an exabyte. So now that
we have adjacency matrices for the worm brain and the human brain, so
comparing the two can give us a scaling factor. For example scaling
factor, S = 7.396 x 10^21 bits / 9.1204 x 10^4 = 8.10929 x 10^16.
Now to estimate the computing power required to simulate a human
brain, B(h), one can simply multiply the byte size of all the software
and data required to simulate the worm and multiply by the scaling
factor: B(h) = S*B(w). Assuming that the levels of redundancy in the
worm brain and human brain are similar we should be able to calculate
the Kolmogorov complexity of the human brain in a similar fashion,
K(h) = S*K(w).
In any case my ability to give an actual estimate, instead of a
methodology to calculate it, is hampered by by inability to locate the
relevant data on the open worm worm project. If somebody out there
knows how big the open worm project software platform and data sizes
are, please post them. Then I could give an actual number that I could
cross correlate with Moore's Law to get an estimate of when the
Singularity might occur.
Those considerations aside, my hats off to the Open Worm Project as
this is a huge stride toward uploading and I am suitably impressed. It
also validates my support for a bottom up simulation strategy.
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