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Artificial Life Forms Evolve Basic Memory, Strategy
Calopteryx notes a New Scientist piece on how digital organisms in a computer world called Avida replicate, mutate, and have evolved a rudimentary form of memory. Another example of evolution in a simulation lab is provided by reader Csiko: "An evolutionary algorithm was used to derive a control strategy for simulated robot soccer players. The results are interesting — after a few hundred generations, the robots learn to defend, pass, and score — amazing considering that there was no trainer in the system; the self-organizing differentiated behavior of the players emerged solely out of the evolutionary process."
When you program some evolutionary theory in your digital world and your digital world is developing some evolutionary lifeform that is news?
Saying there wasn't a trainer in the system is a bit of a misunderstanding really.
Evolutionary algorithms always makes use of a fitness function to define which generations are to survive and evolve and which are to die off, this is the case in the presented setup as well. Without knowing the project i'd guess they let the "teams" play against each other and let the winners survive.
If there wasn't a fitness function it wouldn't really be an evolutionary algorithm, evolution sorta implies "survival of the fittest" and all that you know :) The interesting part is observing the emergent behavior, in other words what we were not expecting to get out of the system. When the system doesn't have any knowledge of what a "defender" is, or what "passing the ball" means, it's interesting to see these well-known patterns evolve even when they are not specified, this is what matters to the AI researcher.
Other implementations of evolutionary algorithms may be fun (http://rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/) but are not showing emergent behavior because you are asking for a specific output through the fitness algorithm. That is the main difference.
Organisms can perfectly draw energy directly from the sun, and animals and humans still do (such as vitamin D production).
As a physician I find your statement ludicrous. While there is a photochemical step in the synthesis of vitamin D it's hardly fair calling a double bond being split by a photon as "drawing energy" from the sun. For that matter you could say that the dimerization of thymine in DNA by sunlight (which produces the genetic damage observed when a person is exposed to UV radiation) is another way we "draw energy" from the sun.
Humans do not produce ATP from sunlight. Period.
And I would agree with OP - all organisms, including plants, are directly dependent on other organisms. Without nitrogen fixing bacteria to fix nitrogen for the plants, and without decomposing bacteria to release minerals again into the soil, even plants would not exist. While the organisms that are set up to harvest sunlight directly from photosynthesis are the biggest input into the food chain, they can't live without the rest of it, especially the lowly decomposers. We're now all totally dependent on one another.
Seven puppies were harmed during the making of this post.
While true, this is also completely meaningless. For even trivial pattern spaces of, say, 512 bits, "long enough" would be far longer than the current age of the Universe.
Forget magic. Any technology distinguishable from divine power is insufficiently advanced.
The problem space is so vast when you get into the necessary details humans take for granted:
Its so vast that it makes secure passwords look simplistic - this is far beyond brute forcing AES encryption. Even a simplified problem space is usually quite large in terms of possible combinations the only advantage AI work has is that there are no singular solutions but a large fuzzy set of solutions that are reasonably acceptable.
Say a monkey typed 99% of Shakespeare but it was wrong only for 1% of it: next attempt being random, the monkey would likely have 0% Shakespeare! There would be no convergence towards the answer. Even bruteforcing encryption rules out past attempts to avoid repeating itself but a random search does not. Furthermore, say the problem space is random - so then a 99% Shakespeare is light years away from the 100% Shakespeare, then no matter what the process for convergence (ie evolution) it is not going to converge which effectively puts you into the same situation as a random search.
The monkey typing thing is a silly way to state the obvious and sound good while doing so. "Its POSSIBLE but impractically time consuming" doesn't sound as good. These AI problems are nothing like monkey's typing - they learn and progress towards competency which is totally different! Again, they do this quite quickly since anything near the monkey approach wouldn't get there in our lifetimes (winning the lotto is more likely.)
Just because it is mindbogglingly complex does not mean it is intelligent...or that it has something we'd normally think of as a "memory" either. Its possible our brains are just pattern matching machines - and since we can only understand the most simple of such things we'll never figure it out (but could build a brain which could figure it out eventually and perhaps our brains are just an extremely fuzzy non-linear pattern match for #42.)
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