AI Built To Hunt Extraterrestrial Intelligence Just Detected 8 New Promising Alien Signals

Eight additional potential indications of extraterrestrial intelligence have been discovered by a machine learning algorithm.

The programme was taught to analyze huge datasets from radio telescopes, specifically looking for signals that could not have a terrestrial origin. It was created by Peter Xiangyuan Ma of the University of Toronto in Canada along with his team.

Massive data sets have been combed through as part of the Breakthrough Listen Initiative and the Search for Extraterrestrial Intelligence (SETI) effort to hunt for indications of technologically advanced civilizations elsewhere in the cosmos. Filtering away the tens of millions of false positives that can be found in these databases is the difficult part. It is now simpler to detect potential signals of interest thanks to the machine learning algorithm created by Xiangyuan Ma and his colleagues, which has been trained to recognize distinctive patterns in the data.

The group examined 480 hours of observations of 820 stars made by the West Virginia-based Robert C. Byrd Green Bank Telescope using the algorithm. The programme found nearly 3 million unique patterns, which were further reduced to only 20,515 by the algorithm. The team found eight promising signs of interest upon ocular assessment.

Five stars that are between 30 and 90 light-years away from Earth are the source of these emissions. HIP 62207, one of these stars, resembles the sun. The signals, however, did not last over time and vanished when the stars were studied again. The team nevertheless recommends additional observations of these targets.

The machine learning-based techno signature search represented by this work is the most thorough one to date. With the help of automated assessments like this one, future research will be easier to organise and our chances of finding alien civilizations may increase. Even though it's unclear where these signals came from, their discovery offers fresh insights into how the cosmos works.

Research paper

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