One of humanity's greatest doubts, the existence of life beyond Earth, has always intrigued many people and scholars. For years, we've been trying to pick up any kind of sound or image signal that might give us clues about the existence of aliens. With the advancement of technology, we get more and more innovative tools to help us in this mission. Recently, the artificial intelligence has been used to try to pick up sound signals from outside the Earth.
AI to discover the existence of extraterrestrials
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Everyone knows that artificial intelligence is already part of our lives, whether in the automation of various applications and programs, or to discover life beyond Earth. Researchers are using AI to try to pick up extraterrestrial signals and try to find evidence of the existence of aliens.
SETI
SETI is the acronym for "Search for Extraterrestrial Intelligence", which would be the search for intelligent life beyond Earth. This study is carried out by researchers who use AI to locate electromagnetic radiation signals coming from a possible advanced civilization outside our solar system.
Telescopes have already been set up for the study from Virginia to the rural plains of Australia, capable of capturing waves and signals. Franck Marchis, planetary astronomer at the SETI Institute, told Nature magazine that this is a new era in SETI research thanks to advances in artificial intelligence.
The biggest challenge, according to the researcher, is that the process of integrating AI into the programs used for them is new, requiring some time to be able to calibrate the equipment correctly with the AI.
At the moment, several data are generated, many of them false-positives, which are generated by waves coming from cell phones, internet, radio and GPS. The goal now is to filter out unnecessary data and increase the accuracy of the equipment and be able to distinguish which signals come from human life and which come from the galaxy.
machine learning
One option found to improve data algorithms is machine learning. Through this technology, it is possible to “teach” computers to recognize the resources that are terrestrial interference and differentiate them from space signals, allowing filtering and data collection correct.
