

Estimating the energy cost of evolution - evaneykelen
http://alanwinfield.blogspot.com/2014/07/estimating-energy-cost-of-evolution.html

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skywhopper
This is an interesting and valuable analysis. But while applying selection and
mutation to generate software might be a fun problem to tackle, it seems like
a terrible way to produce useful software.

As a model, the evolution of human intelligence is not something we know
remotely enough about to reproduce artificially. Our ancestors evolved in
environments that were constantly changing. They had social relationships with
other creatures of their kind. They competed with other organisms. They were
predators and prey. The path from the first multicellular organisms to the
humans of today was not a straight one.

How would you go about judging the evolutionary suitability for reproduction
of a particular individual instance of the software? Not to mention that sex
surely plays a role in our development. How do you model sexual reproduction
and the recombinatorial process of mixing genes from the parents? How are the
parents to judge the suitability of each other for mating? The feedback loop
of mating behavior, sexual selection, and human intelligence is not a minor
thing.

What about development? Humans are created through a process. Our genes alone
do not specify our composition. There is feedback from the environment, from
our nutrition, from the symbiotic organisms that live in our guts and on our
skin, from our social relationships, from our parenting, from what skills we
learn, and what sports we play, and which books we read, all of which manifest
physical changes on our bodies that are not specified in our genes.

I cannot envision a situation where coming up the algorithm that could
successfully produce an intelligent piece of software would not be far more
complicated and impossible to create than the resulting intelligent software.

But if it were possible to create this software by this method, how
inefficient it would be. Ask any evolutionary biologist how efficient natural
selection is at coming up with ideal solutions to problems. There are plenty
of ingenious inventions generated by natural selection, but very few if any
are remotely "efficient". And the process of generating those systems via
thousands and millions of generations of self-replicating organisms is about
the least efficient imaginable system possible, as demonstrated by this paper.

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dirtyaura
When you claim that to evolve an intelligent agent, the evolutionary algorithm
itself needs to be more intelligent, you are essentially arguing for
intelligent design. In the light of modern science, this is clearly wrong. The
world is full of emergent complex phenomena (such as intelligent humans) that
are result of several simpler "rules".

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Strilanc
You're confusing things that are good when explaining with things that are
good when optimizing.

Simplicity is a huge explanatory advantage, because simple things generally
have exponentially higher prior probabilities. But simplicity is only a minor
advantage, or even a disadvantage, when you want to make something efficient.
It's too constraining.

The dumb algorithm still _works_... it just takes longer. Nature took
nonillions of cells and trillions of generations to make something
intelligent; we'd prefer something a bit less brute force.

~~~
icegreentea
Well, remember that intelligence (in the form that we would apparently like to
develop) evolved as a by product of natural selection. For one thing, our
level of intelligence only really makes sense once a whole set of other niches
have been filled out.

Applying a better selection/objective function to an otherwise 'dumb' process
would likely drastically reduce the cost to reach a 'solution'.

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sebastianconcpt
Estimating the energy cost of helping to build the Transhumanist hellish
Roko's Basilisk
[http://www.slate.com/articles/technology/bitwise/2014/07/rok...](http://www.slate.com/articles/technology/bitwise/2014/07/roko_s_basilisk_the_most_terrifying_thought_experiment_of_all_time.html)

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abecedarius
IIRC the thermodynamic lower bound is ln 2 kT per bit of final output; for the
human genome size that's well under 10^-10 J. Reversible computing may be far
off, but I wouldn't assume it's farther off than evolving our successors. (The
paper doesn't mention any of this.)

