AI Built to Find Aliens Just Picked Up EIGHT Alien Radio Signals From Space

Until recently, astronomers have had a hard time separating likely alien signals from those produced by humans.

AI Built to Find Aliens Just Picked Up EIGHT Alien Radio Signals From Space

Thanks to a new artificial intelligence-trained system, eight unexplained radio signals have already been found, which experts say could speed up the hunt for extraterrestrial life.

After using the program to examine 820 stars in a region of space previously thought to be devoid of possible alien activity, experts led by University of Toronto student Peter Ma uncovered the surprising finding.

Previous analyses of the data had missed uncertain signs.

Part of the reason, Ma explains, is that 'there is a lot of interference in many of our observations.

We need to distinguish the exciting radio signals in space from the uninteresting radio signals from Earth.
Strange: This graphic shows the eight signals of interest. They are the ones that appear orange
Strange: This graphic shows the eight signals of interest. They are the ones that appear orange

Working with astronomers from the SETI Institute, Breakthrough Listen, and scientific research institutions around the world, Ma developed a new machine learning method that can better distinguish possible extraterrestrial signals from all the background noise on our planet.

It involved the use of deep learning, a type of artificial intelligence and machine learning that models how humans acquire specific knowledge and is a critical component of autonomous cars.

In this case, researchers effectively used machine learning to train a traditional algorithm from a simpler computer to distinguish between likely extraterrestrial signals and those caused by humans.

When the current program previously examined radio data from a collection of stars collected by the Robert C. Byrd Green Bank Telescope in West Virginia, it had found nothing.

But Ma and his colleagues have already detected as many as eight separate radio signals emanating from that region of space.

Steve Croft, project scientist for Breakthrough Listen at the Green Bank Telescope, added: 'The key problem with any techno-signature search is sifting through this huge haystack of signals to find the needle that might be a transmission from an alien world.

The vast majority of signals detected by our telescopes come from our own technology: GPS satellites, cell phones and the like.

Peter's algorithm gives us a more effective way to filter the haystack and find signals that have the characteristics we expect from technosignatures.

The eight signals appear to be coming from five of the 820 stars in the group, located in directions ranging from 30 to 90 light-years away.

Researchers need more time to pinpoint the likely source of the radio signals.

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