Will machine learning help us find extraterrestrial life?

When pondering the probability of discovering technologically advanced extraterrestrial life, the question that often arises is, "if they're out there, why haven't we found them yet?" And often, the response is that we have only searched a tiny portion of the galaxy. Further, algorithms developed decades ago for the earliest digital computers can be outdated and inefficient when applied to modern petabyte-scale datasets. Now, research published in Nature Astronomy and led by an undergraduate student at the University of Toronto, Peter Ma, along with researchers from the SETI Institute, Breakthrough Listen and scientific research institutions around the world, has applied a deep learning technique to a previously studied dataset of nearby stars and uncovered eight previously unidentified signals of interest. "In total, we had searched through 150 TB of data of 820 nearby stars, on a dataset that had previously been searched through in 2017 by classical techniques but labeled as devoid of interesting signals," said Peter Ma, lead author.