AI unveils 90 pc accurate test for extraterrestrial life

Scientists have unveiled a remarkable AI-based method for detecting signs of past or present life on other planets, heralded as the “holy grail of astrobiology.” The findings, published in the Proceedings of the National Academy of Sciences, stem from the collaborative efforts of a team comprising seven researchers led by Jim Cleaves and Robert Hazen from the Carnegie Institution for Science, generously funded by the John Templeton Foundation. This research promises to reshape our understanding of life’s diversity and its potential existence beyond our home planet.

This revolutionary analytical technique holds the promise of revolutionizing the quest for extraterrestrial life while enhancing our comprehension of the origins and chemistry of early life on Earth. Dr. Hazen, one of the study’s authors, believes this method could pave the way for employing smart sensors on robotic spacecraft, landers, and rovers to seek signs of life before samples are returned to Earth.

One immediate application of this novel test could be unraveling the mysteries surrounding ancient Earth rocks, including samples collected by NASA’s Mars Curiosity rover’s Sample Analysis at Mars (SAM) instrument. By adapting their method to align with SAM’s protocols, scientists hope to determine if there are organic molecules on Mars that originated from a Martian biosphere.

The significance of this research extends beyond our cosmic neighborhood. Lead author Jim Cleaves emphasizes three key takeaways: firstly, it underscores fundamental distinctions between biochemistry and abiotic organic chemistry; secondly, it demonstrates the capacity to discern the previous existence of life on Mars and ancient Earth samples; and thirdly, it hints at the ability to differentiate alternative biospheres from Earth’s, bearing profound implications for future astrobiology missions.

Unlike conventional approaches that focus on identifying specific molecules, this innovative method employs artificial intelligence to distinguish between biotic and abiotic samples by recognizing subtle variances within a sample’s molecular patterns. This process involves pyrolysis gas chromatography analysis, which separates and identifies a sample’s components, followed by mass spectrometry, which determines their molecular weights.

The AI was trained using extensive multidimensional data derived from molecular analyses of 134 known carbon-rich samples, whether biotic or abiotic. Remarkably, the AI achieved an accuracy rate of approximately 90%, successfully distinguishing samples derived from living organisms, remnants of ancient life, or those with abiotic origins.

Dr. Hazen highlights the unexpected revelation that this method identified signs of preserved biology in some samples over hundreds of millions of years, despite significant decay and alteration. This groundbreaking insight opens the door to detecting alien biochemistries, fundamentally different from Earth’s, if life forms are discovered elsewhere.

In essence, this method seeks patterns in molecular distributions that arise from life’s need for “functional” molecules, offering the potential to distinguish even photosynthetic life or eukaryotes (cells with a nucleus). The implications extend beyond astrobiology, promising applications in fields like biology, paleontology, and archaeology.

As Dr. Hazen aptly summarises, “It’s as if we are just dipping our toes in the water of a vast ocean of possibilities.”