Alien hunting goes crowd-sourced with SETILive

Feb 29, 2012
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While the Search For Extra Terrestrial Life (SETI) may not be quite as flush as it used to be, its organizers are finding new and interesting ways to continue the search for life among the stars. Their latest initiative is SETILive, a crowd-sourced web application that lets anyone join the search of the nearby universe, no advanced degrees required. The SETILive website allows registered users to scan automatically-generated images based on radio frequency scans of sections of space that SETI believes are the likeliest to contain extraterrestrial life.

This isn't just a worldwide digital field trip: SETI believes that under the right circumstances, the human eye may be a better tool than their massive computer arrays for analyzing this particular set of data. Considering that the scientists involved don't actually know exactly what an alien radio signal might look like even if they found it, it seems like a valid enough tactic. A single user can't sound the UFO alarm alone; if enough users report possible extraterrestrial activity on a single radio frequency image, SETI's telescopic radio arrays will automatically re-scan the area and alert on-staff scientists to the crowdsourced findings.

Less than a year ago the SETI program was in dire straits, with budget cutbacks temporarily shutting down the bulk of their expensive and mostly government-funded search. Thankfully at least some of their funding has been re-appropriated back to the program, and the search continues. This isn't the first time that the program has appealed to the public for distributed assistance: the SETI@home program has been using a network of thousands of home computers to augments the processing power of SETI's own hardware for over a decade. Participants allow a portion of their computer's idle computing strength to be lent to SETI over a virtual private network.

SETILive is a very similar idea, with the notable difference that participants are lending their own down-time. A small social network is already being built around the service, with Foursquare-style badges and achievements. At present there's anywhere from 50-100 people actively scanning photos at once, with over twenty thousand classified entries in the system already.

[via Slashdot]


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