Scientists Discover 8 Mysterious Radio Signals
There is a question that humanity has been wondering for thousands of years: Are we alone in the universe? There is no answer to this question yet, but the best way to find out is to detect techno-signals that alien civilizations may have developed. Until now, scientists have always had trouble distinguishing between potential extraterrestrial signals and those of human origin. Canadian researchers have discovered 8 mysterious radio signals by developing a new artificial intelligence algorithm that they hope will facilitate the search for aliens.
There is a question that humanity has been wondering for thousands of years: Are we alone in the universe? There is no answer to this question yet, but the best way to find out is to detect techno-signals that alien civilizations may have developed. Until now, scientists have always had trouble distinguishing between potential extraterrestrial signals and those of human origin. Canadian researchers have discovered 8 mysterious radio signals by developing a new artificial intelligence algorithm that they hope will facilitate the search for aliens.
Experts led by University of Toronto student Peter Ma in Canada detected 8 radio signals using an artificial intelligence algorithm they developed to look at 820 stars in a space field previously thought to be devoid of any potential extraterrestrial activity.
These vague signals had been overlooked in previous reviews, Ma said. “We need to separate the exciting radio signals from space from the uninteresting radio signals from Earth,” Ma said, adding that one of the reasons is “too much interference in most of the observations.” aforementioned.
A NEW TECHNOLOGY IS DEVELOPED
Together with the SETI Institute, Breakthrough Listen, and astronomers from scientific research institutions around the world, Ma has developed a new machine learning algorithm that can better pick out potential alien signals from all the background noise on Earth.
This algorithm involved using deep learning, a type of machine learning, and artificial intelligence, a key technology in self-driving cars, that mimics the way humans acquire certain types of information.
CAN DISCRIMINATE FOREIGN AND WORLD SIGNALS
In this case, the researchers essentially took a classical algorithm from a simpler computer and used machine learning to teach them to distinguish between potential alien signals and signals of human origin.
The current algorithm found nothing when it scanned radio data from dozens of stars previously collected by the Robert C. Byrd Green Bank Telescope in West Virginia. But instead of finding anything of interest in that part of space, Ma and his colleagues discovered eight different radio signals coming from there.
Scientist Steve Croft, who is involved in the Breakthrough Listen project in Green Bank Telescope, said in a statement on the subject:
“The key issue in any techno-signature research is looking at these huge piles of straw signals to find the needle that could 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 it offers us a more efficient way to filter in the haystack and find signals with the characteristics we expect from techno signals.
On the other hand, the researchers said that the 8 new signals detected may have come from five of the constellation of 820 stars 30 to 90 light-years away. The signals have not been proven to be extraterrestrial, but the researchers announced that the technology they developed will open the door to many scientific studies.
The research was published in the journal Nature Astronomy.
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