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Scientists Develop AI Capable of Detecting Extraterrestrial Life

Scientists have created an artificial intelligence (AI) program that can detect alien life in physical samples — though they aren’t sure exactly how it works.

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Utilizing a novel machine-learning algorithm, which was trained using various sources such as living cells, fossils, meteorites, and synthesized chemicals, the researchers report that the AI can differentiate between samples originating from biological and non-biological sources with an accuracy rate of 90%. Nevertheless, the algorithm’s internal processes remain shrouded in mystery.

The researchers propose that this innovative test could be deployed almost immediately for tasks such as probing for signs of life on Mars, leveraging data obtained from Martian rock samples gathered by the Curiosity rover.

Additionally, it holds the potential to shed light on the origins of enigmatic ancient rocks discovered on Earth. The team’s findings were disclosed on September 25th in the journal PNAS.

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“These results mean that we may be able to find a lifeform from another planet, another biosphere, even if it is very different from the life we know on Earth,” study co-lead author Robert Hazen, an astrobiologist at the Carnegie Institution for Science in Washington, D.C., said in a statement.

“And, if we do find signs of life elsewhere, we can tell if life on Earth and other planets derived from a common or different origin.

“Put another way, the method should be able to detect alien biochemistries, as well as Earth life,” he added.

“That is a big deal because it’s relatively easy to spot the molecular biomarkers of Earth life, but we cannot assume that alien life will use DNA, amino acids, etc. Our method looks for patterns in molecular distributions that arise from life’s demand for ‘functional’ molecules.”

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Jake Carter

Jake Carter is a researcher and a prolific writer who has been fascinated by science and the unexplained since childhood. He is always eager to share his findings and insights with the readers of, a website he created in 2013.