Machine learning to find learned aliens
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Machine learning could aid in the search for signs of intelligent alien life in the universe, according to a study published Monday.
Why it matters: Searching for radio signals emitted by technologically advanced extraterrestrial societies requires scanning large portions of the sky with powerful radio telescopes, producing a lot of data scientists need to parse through.
- Machine learning tools could make that job easier.
Driving the news: A new study published in Nature Astronomy this week details the use of an algorithm that helped researchers sift through data previously analyzed in 2017.
- The machine learning tool was trained to differentiate radio signals that might originate in distant star systems from human-created sources like cell phones and satellites.
- The tool turned up eight new radio signals of interest — possible signs of intelligent extraterrestrial life — within the dataset. Those signals came from five different stars that are 30 to 90 light-years away.
But, but, but: Those signals don't mean they found aliens.
- Brief follow-up observations didn't turn up a repeat signal, and it's still possible these eight targets of interest were created by chance, not emitted by alien civilizations.
- More observations and analysis are now being conducted, according to a press release from the University of Toronto.
The big picture: Scientists may need machine learning for these types of searches in the future.
- "With our new technique, combined with the next generation of telescopes, we hope that machine learning can take us from searching hundreds of stars, to searching millions," one of the authors of the study Peter Ma, of the University of Toronto, said in the press release.
