- Mike van der Noordt
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Combining the puzzlepieces.
After almost 20 years since Karl Sims worked on computational evolution, we would have expected a greater complexity in results. After some reading the main reason for this slow-down appears to be the fact it worked with rigid primitives and limited algorithms.
Now, however, the creation of voxelbased models with multiple materials are being researched. And a different approach to encoding (Compositional Pattern-Producing Networks(?)). It seems that the greatest hurdle is computational power (?).
In research about mapping the brain, it also seems that computerpower is the biggest brake on development. But nonetheless already we start to understand the mechanics of memory, processing information (?). (I guess also a great hurdle is legislation(?)). My hunch is that not only pure computional processes in the brain will be mapped out, but eventually also the way emotions work, like aggression, love, empathy (?)
Then we have the genome project(s).
We have nanotechnology on a cellular level (biotechnology(?))
We have 3D printing, now on an almost atomic level, and more materials which can be used are added to the list on a regular basis.
We have the stemcell research; building tissue, manipulating our buildingblocks.
We have cloud computing, maybe eliminating the big hurdle of raw computerpower.
To me as a noob, it seems that if we put all this science in the mix, we're talking about self-replicating, (soft-(?)) robots, adapting to any environment, able to utilize and manipulate elements on a cellular, or even molecular level, mimmicking, biologic functions etc. etc.
I'm not a scientist, and don't have any background in any of these fields (the reason for all the questionmarks :)), so please correct me if i'm wrong, and please add some of your thoughts and knowledge about the subject(s), mainly how different fields of science can be, or actually are being, combined to speed up this progress? And could be the common problem computing power?
Thanks in advance.