The artificial intelligence detects 72 mysterious flashes from the distant galaxy

Although many space scientists and experts have warned against the use of artificial intelligence many times, a group of scientists have used AI to uncover 72 previously unknown mysterious signals, called billions of dollars. light-years across the space.

The Breakthrough Listen project, which is a scientific program aimed at searching for intelligent alien communications, has reported these rapid fire signals. Although the origins of these signals are unknown, scientists have speculated that some of them originated from neutron stars located near black holes, interstellar clouds or nebulae. According to some experts, these mysterious signals could be a sign of extraterrestrial life. The scientists said that a particular signal, FRB 121102, had been detected more than once.

Researchers involved in Breakthrough Listen have used the world's largest fully controllable radio telescope, the Green Bank Telescope in West Virginia, to investigate the FRB in August 2017. Initially, based on five-hour data collected by Vishal Gajjar, UC Berkeley and his team found 21 shards from a galaxy, which is three billion years old.

Now, scientists have come up with a machine learning algorithm, a really useful technology for optimizing search engines and sorting images. This tool forced tens of additional FRBs from the same dataset. Gerry Zhang, a UC Berkeley PhD student and his colleagues' neural network algorithm, screened around 400 terabytes of data to reveal additional FRBs.

While the two research articles of Zhang and Gajjar were accepted for publication in The astrophysical journal, the new results of these projects have suggested that these mysterious explosions are not regularly received and that this information will help scientists to clarify possible explanations of FRB sources.

In a Breakthrough Listen statement, Zhang said it was only the beginning of using these powerful methods to discover radio transits and "we hope our success will inspire other serious efforts to apply machine learning to radioastronomy ".

Andrew Siemion, director of the Search for Extraterrestrial Intelligence (SETI) research center and lead researcher, said Zhang's work is "exciting, not only because it helps us understand the dynamic behavior of the FRB, but shows the use of machine learning to detect signals missed by conventional algorithms.

It should be known that scientists have recently used the Canadian hydrogen intensity mapping (CHIME) experiment to search the FRB in the sky and hope that the telescope will improve the number of these mysterious flashes traveling in space.

However, many experts have asserted that it is possible that these signals do not indicate the existence of extraterrestrial intelligence in the universe. Previously, Newsweek reported that Gajjar did not think these signals came from distant foreign civilizations because gusts "occur everywhere in the sky and show similar properties". He added that if these entities really wanted to get in touch with humans could have altered these signals as the FRB to communicate their artificial nature.

It should be noted that scientists have created a special Richter-scale tool for detecting extraterrestrial signals, which would prove whether a person in space is actually trying to contact humans or not. The new scale is an improved version of the existing Rio scale, which is already used by foreign hunters, but the new scale, called Rio 2.0, assigns scores to signals detected by Search for Extraterrestrial Intelligence (SETI).