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AI machine designed to detect alien in space has discovered eight promising signals
Home>Technology>Space
Published 07:53 4 Aug 2023 GMT+1

AI machine designed to detect alien in space has discovered eight promising signals

Scientists tasked the machine to listen to humungous amounts of data and it came up with some interesting insights.

Velentina Boulter

Velentina Boulter

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Featured Image Credit: Pallava Bagla/Getty Images. Bettmann /Getty Images

Topics: Space, News, Technology, Aliens

Velentina Boulter
Velentina Boulter

Velentina is a freelance journalist for LADbible who is currently studying journalism at The University of Melbourne. When she's not typing away at her laptop, she can usually be found overanalysing movies or making terrible jokes.

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Eight signals of potential extraterrestrial life have been detected by an AI machine used by international scientists.

The Breakthrough Listen project, which this new research contributed towards, aims to search deep space for signs of extraterrestrial life by looking out for radio signals or other transmissions that alien life might be sending us.

Considering most signals end up being false positive, some researchers have designed an AI machine to help them sort through all the potential alien signals much faster than before.

Photo
Samuel de Roman/Getty Images

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The AI works as an algorithm sorting through data from radio telescopes, searching for signals of interest that may have come from another life form.

The team, led by Peter Ma from the University of Toronto, is a part of the Search for Extraterrestrial Intelligence project known as SETI.

Their research was conducted across 820 different stellar targets using the Green Bank Telescope in West Virginia.

Their results, which analyzed over 480 hours of observations, were published in Nature Astronomy earlier this year.

Of all the data they analyzed, there were eight signals which the AI detected that were 'promising extraterrestrial intelligence signals of interest not previously identified'.

While the team was not prepared to make definite conclusions about the causes of the signals, they said the research proved AI was on the right track.

“This machine-learning approach presents itself as a leading solution in accelerating SETI and other transient research into the age of data-driven astronomy," they said in a statement.

“As it stands, our model represents a comprehensive Machine Learning-based technosignature search.

Photo
ANDREW CABALLERO-REYNOLDS/AFP via Getty Images

“It improves on previous work by finding signals of interest not detected before.”

However, because we have never found a genuine extraterrestrial radio signal, it’s hard for researchers to base an algorithm on something we’ve never found.

According to Professor Michael Garrett, the machine is likely looking out for a few characteristics such as narrow bands, disappearing when the telescope moves in another direction, and Doppler drifting.

Doppler drifting is a pattern that would occur because our planet and the potential extraterrestrial planet are both moving.

Even though they gave no conclusion as to what the eight signals were, the team called for more follow-up.

“We encourage further re-observations of these targets," they said.

Whether or not the signals are genuine, this breakthrough AI takes us one step closer to learning whether we are alone in the universe or not.

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