New AI algorithm can detect signs of life with 90% accuracy. Scientists want to send it to Mars

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Sharmila is a Seattle-based science journalist. She found her love for astronomy in Carl Sagan's The Pale Blue Dot and has been hooked ever since. She holds an MA in Journalism from Northeastern University and has been a contributing writer for Astronomy Magazine since 2017. Follow her on Twitter at @skuthunur.

) hold on to information about the chemical processes that made them. This is likely to hold true for alien life, too, according to the new study.

On any world, life may produce and use higher quantities of a select few compounds to function on a daily basis. This would differentiate them from abiotic systems — and it is these differences that can be spotted and quantified with AI, the researchers said in the statement. The team first trained the machine learning algorithm with 134 samples, of which 59 were biotic and 75 were abiotic. Next, to validate the algorithm, the data was randomly split into a training set and a test set. The AI method successfully identified biotic samples from living things like shells, teeth, bones, rice, human hair as well as from ancient life preserved in certain fossilized fragments made of things like coal, oil and amber.

The tool also identified abiotic samples including chemicals like amino acids that were created in a lab as well as carbon-richAlmost immediately, the new AI method can be used to study the 3.5 billion-year-old rocks in the Pilbara region in Western Australia, where the world's oldest fossils are thought to exist. First found in 1993, these rocks were thought to be fossilized remains of microbes akin to cyanobacteria, which were the first living organisms to produce oxygen on Earth.

 

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