University of Toronto undergrad develops AI technique to accelerate the search for extraterrestrial life

Peter Ma, a member of Victoria College, developed an AI algorithm used by an int
Peter Ma, a member of Victoria College, developed an AI algorithm used by an international group of researchers to help speed up the search for signals generated by extraterrestrial life
Peter Ma, a member of Victoria College, developed an AI algorithm used by an international group of researchers to help speed up the search for signals generated by extraterrestrial life Are we alone in the universe? With the help of artificial intelligence, scientists may be one step closer to finding the answer. Led by researchers at the University of Toronto, an international team of scientists has streamlined the search for extraterrestrial life by using a new algorithm to organize the data from their telescopes into categories to distinguish between real signals and interference. Through an AI process known as machine learning, the new approach allows the researchers to quickly sort through the information and find patterns. Since the 1960s, astronomers working on "SETI" (the Search for Extraterrestrial Intelligence) have used powerful radio telescopes to search thousands of stars and hundreds of galaxies for so-called "technosignatures," or technologically-generated signals, on the assumption that an advanced extraterrestrial civilization would be sophisticated enough to emit such signals. Yet, despite the fact that the telescopes used for these searches are located in areas where there is minimal interference from technology like cell phones and TV stations, human disturbance still poses major challenges.  "In many of our observations, there is a lot of interference," says Peter Ma , a U of T undergraduate student studying math and physics in the Faculty of Arts & Science who is first author on a new research paper  published in Nature Astronomy  that explains the technique.
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