AI helps scientists search for life on other planets

Scientists have developed a new method using artificial intelligence to identify life on other planets.

A group of researchers has said it can now be determined with 90 per cent accuracy if a sample is biological or non-biological.

The simple and reliable test could revolutionise the search for life on other planets, the researchers say.

“This is a significant advance in our abilities to recognise biochemical signs of life on other worlds,” said lead researcher Robert Hazen, of the Carnegie Institution’s Geophysical Laboratory and George Mason University in the US.

“It opens the way to using smart sensors on unmanned spaceships to search for signs of life.

“This routine analytical method has the potential to revolutionise the search for extraterrestrial life and deepen our understanding of both the origin and chemistry of the earliest life on Earth.

“It opens the way to using smart sensors on robotic spacecraft, landers and rovers to search for signs of life before the samples return to Earth.”

The scientists say that most immediately, the new test could reveal the history of mysterious, ancient rocks on Earth, and possibly that of samples already collected by the Mars Curiosity rover’s Sample Analysis at Mars instrument.

“We’ll need to tweak our method to match SAM’s protocols, but it’s possible that we already have data in hand to determine if there are molecules on Mars from an organic Martian biosphere,” said lead author Jim Cleaves of the Earth and Planets Laboratory, Carnegie Institution for Science in Washington.

“The search for extraterrestrial life remains one of the most tantalising endeavours in modern science.”

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The method does not rely simply on identifying a specific molecule or group of compounds in a sample.

Instead, the researchers demonstrated that AI can differentiate between living and non-living samples by detecting subtle differences within a sample’s molecular patterns.

The scientists used Nasa flight-tested methods to analyse 134 varied carbon-rich samples from living cells, age-degraded samples, geologically processed fossil fuels, carbon-rich meteorites, and laboratory-made organic compounds and mixtures.

Fifty-nine of these were of biological origin (biotic), such as a grain of rice, a human hair and crude oil, and 75 were of non-biological origin (abiotic), such as lab-made compounds like amino acids or samples from carbon-rich meteorites.

Using a suite of machine-learning methods, the researchers created a model that can predict the abiotic or biotic nature of the sample with around 90 per cent accuracy.

Surprisingly, in spite of significant decay and alteration, the new method detected signs of biology preserved in some instances over hundreds of millions of years.

“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,” Dr Hazen said.

“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.

“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.”

The findings have been published in the Proceedings of the National Academy of Sciences.

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