Machine Learning Detects Anomalies in Radio Signals

A team at the University of Toronto have developed a machine learning algorithm. It can comb through thousands of signals of interest which SETI telescopes return to reduce false positives. And they can even look for patterns in radio signals other algorithms would miss. I spoke with Cherry and Peter Mar to hear how they've done it.