Scientists working on SETI, the search for extraterrestrial intelligence, have turned a student project into a powerful AI-based tool for spotting radio signals that could have been generated by an alien civilization. When presented with a trove of real data, the algorithm flagged eight such examples that had previously been missed when the same data were analyzed using more conventional means.
It was then that Mr. Ma contacted SETI scientists at the University of California, Berkeley, to ask for technical details about their open-source data, which he had been working with for his project. The conversation led to a summer job and then further development of his machine learning SETI algorithm, which he continued while at U of T.
A key challenge in hunting for signs of alien intelligence is that no one knows what a true signal will look like. That means the algorithm had to teach itself to see signals that simply look out of the ordinary when compared with the flood of radio energy that reaches the sensitive antenna from across the universe and from closer to home.
It identified eight candidate signals that had been overlooked in earlier analyses. The signals appear to originate from five different stars located between 30 and 90 light years from our solar system. Follow-up observations conducted last year did not confirm any repeat transmissions, which means the detections were likely false positives.
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