Searching the skies for UFOs or homesick aliens is practically an American pastime, and no one does it better than the SETI Institute (SETI meaning Search for Extraterrestrial Intelligence).
Established in 1984, SETI has made it their mission to scan the skies for radio signals comprised of non-Earth based “technosignatures” that may belong to alien tech. Such signals—which may indicate communications technology in use, and thus intelligence—are sought after by scientists looking for signs of alien life. So far, this decades-long search has yet to turn up any convincing leads, but a new paper published Monday in the journal Nature Astronomy is hoping to change that by using machine learning to tackle the problem…
Peter Ma is first author on the paper and an undergraduate student at the University of Toronto. He told Motherboard in an email that while AI has been applied to SETI’s radio data in the past, this new approach takes the search completely out of human hands.
“Previously people have inserted ML [machine learning] components into various pipelines to help with the search,” Ma said. “This work relies entirely on just the neural network without any traditional algorithms supporting it and produced results that traditional algorithms did not pick up.”
Our knowledge grows. Methods improve. Understanding information gathered is the next task.