ALONESIA.COM – A group of scientists led by the NASA Astrobiology Institute (NAI) SETI Institute team recently released a study. It details how machine learning can be used to more efficiently pinpoint where life might be lurking on the red planet, Mars.
Scientists decided to run experiments about Mars in a region known as the Salar de Pajonales—and an area that lies where the Atacama Desert meets the Altiplano is known to be inhospitable to life.
However, it’s not uninhabitable—considered a good Earth substitute for the Martian surface. Using a combination of still images, samples, and drone footage, the team mapped the distribution of life in the sparsely inhabited region.
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Researchers then bring that data back to the lab for use in artificial intelligence (AI) training.
The goal is to teach the computer to recognize which areas have the highest chance of harboring life—such as a certain small group of geological features or a rare water source—and be able to extrapolate that data to other locations.
In theory, once the AI learns what details indicate life in the Salar de Pajonales, it should be able to use those patterns to find the areas with the best chance of harboring life in any terrain. It worked really well.
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Once AI learns what it needs to recognize, researchers can combine machine learning with collected statistical ecological data to find signs of life 85 percent of the time it exists.
Without the help of AI, the team was only able to find less than 10 percent of the biosignature.
You can imagine how helpful the search for life on the surface of Mars will be. Presently, explorers we sent to our next-door neighbor planet land and search for life as they drive along their paths.
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Meanwhile efforts were made to select landing sites that had a strong chance of harboring life.
Unlike an explorer who is able to micro-target the best and most promising regions while exploring the planet he is driving. around.
