A new AI-based method shows promising results in helping us find signs of life on other planets. Researchers called the newly discovered AI (artificial intelligence) algorithm the "holy grail of astrobiology."
New AI-Based Method Revolutionizes Search for Alien Life
A team of scientists led by Carnegie's Robert Hazen and visiting scholar Jim Cleaves of the Tokyo Institute of Technology and the Blue Marble Space Institute for Science recently discovered an accurate test for signs of life on other planets with 90% accuracy.
Their method, based on artificial intelligence, separated biological samples from the present and the past from those of abiotic origin. The new test accurately ascertains whether anything formerly alive has ever been a part of the history of a sample.
According to Hazen, this common analytical technique can transform the search for alien life and advance our knowledge of the chemistry and origin of the first life on Earth. It allows looking for evidence of life before the samples are sent to Earth utilizing intelligent sensors aboard robotic spacecraft, rovers, and landers.
The new test will provide light on the past of enigmatic, ancient rocks found on Earth and samples previously acquired by the Sample Analysis at Mars (SAM) instrument on the Mars Curiosity rover.
According to lead author Cleaves, the quest for extraterrestrial beings continues to be one of science's most alluring projects. There are many ramifications of this new research, but there are three main components - first, biochemistry differs from abiotic organic chemistry at a fundamental level; second, we can determine whether ancient Mars and Earth samples were once home to life; and third, it is likely that this new method could distinguish other biospheres from those of Earth, with important ramifications for future astrobiology missions.
How Does the New AI Method Work?
The novel analytical approach relies on more than identifying a particular molecule or a sample's compositional group. Instead, by identifying subtle differences in a sample's molecular patterns as revealed by pyrolysis, gas chromatography analysis-which separates and identifies a sample's parts, followed by mass spectrometry-which establishes the molecular weights of those components. The researchers showed that AI could distinguish biotic from abiotic samples.
The origin of a new sample was trained using a vast amount of multidimensional data from the molecular analyses of 134 known abiotic or biotic carbon-rich samples. It has successfully differentiated samples with abiotic origins, remains of extinct life altered by geological processing, and samples from living creatures.
The scientists explain that because groupings of organic molecules, whether biotic or abiotic, tend to deteriorate with time, it has been challenging to pinpoint the origins of many ancient carbon-bearing materials. Surprisingly, the new analytical technology found evidence that biology survived in some cases across hundreds of millions of years despite severe decay and modification.
Using this method, scientists may soon be able to explain the origin of the 3.5 billion-year-old black sediments from Western Australia. These rocks have been the subject of intense discussion since some scientists believe they contain the planet's oldest fossilized bacteria, while others assert that they are devoid of any traces of life.
Hazen believes that AI could do more as it can easily differentiate abiotic from biotic and modern from ancient. He added that we are just dipping our toes in the water with a vast ocean of possibilities.
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