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SETI Institute Is Looking For a Few Good Algorithms
blackbearnh writes "For years, people have been using SETI@Home to help search for signs of extraterrestrial life in radio telescope data. But Jill Tarter, director of the Center for SETI Research at the SETI Institute, wants to take things to the next level. Whereas SETI@Home basically used people's computers as part of a giant distributed network to run a fixed set of filters written by SETI researchers, Tarter thinks someone out there may have even better search algorithms that could be applied. She's teamed with a startup called Cloudant to make large volumes of raw data from the new Allen telescope available, and free Amazon EC2 processing time to crunch the data. According to Tarter: 'SETI@Home came on the scene a decade ago, and it was brilliant and revolutionary. It put distributed computing on the map with such a sexy application. But in the end, it's been service computing. You could execute the SETI searches that were made available to you, but you couldn't make them any better or change them. We'd like to take the next step and invite all of the smart people in the world who don't work for Berkeley or for the SETI Institute to use the new Allen Telescope. To look for signals that nobody's been able to look for before because we haven't had our own telescope; because we haven't had the computing power.'"
Any sufficiently advanced technology is indistinguishable from noise. I remembered hearing this in school ...
Well, to be more precise, it follows as an implication of:
1) Sufficiently advanced technology is indistinguishable from magic. (Clarke's 3rd Law.)
2) Maximally compressed data is indistinguishable from noise. (Theorem in information theory.)
A sufficiently advanced civilization will ("magically") hit the theoretical compression maximum, and that will look like random noise. (Anyone's head hurting yet?)
Information theory is life. The rest is just the KL divergence.
If you take truly compressed data, which resembles uniform noise, you will see a uniform distribution, not the one described in Zipf's law.