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Big Data: Scanning Radio Astronomic Data for ET
SETI@home (Search for ExtraTerrestrial Life), a 20-year old experiment to search for life beyond our earth, was retired at the end of March. The idea for the project was first conceived in 1995 by computer scientist David Gedye and ultimately rolled out in 1999. It was the original crowdsourcing idea, a way to capture capture massive numbers of unused cycles from idle computers, creating a distributed supercomputer.
Over the last twenty years, the project has collected massive amounts of radio astronomy data by computers volunteered by people from all over the world. No evidence of any extraterrestrials have been found yet, but the probability may be increasing. Andrew Siemion, directory of the Berkeley SETI project said that the probability that ET evidence will be found is 1000 times greater in the coming decade compared to 2011-2021.
The search for ET isn’t over, but the tools are changing. Faster computers and data processing techniques like Big Data will be employed to continue the search.
Jill Tarter, astronomer from the SETI project, said that “the ability to use machine learning to help us find signals in noise I think is really exciting. Historically we’ve asked a machine to tell us if a particular pattern in frequency and time could be found. But now we’re on the brink of being able to say to the machine, ‘Are there any patterns in there?’”
Siemion said that “I think there’s something particularly romantic about the idea of machine learning and artificial intelligence looking for extraterrestrial intelligence which itself might be artificially intelligent.”
