A groundbreaking AI system, LifeTracer, developed by Georgia Tech and NASA’s Goddard Space Flight Center, addresses the complex question of whether certain chemistry originates from life. This machine learning tool, which analyzes organic molecules in meteorites and Earth soils, has achieved an 87% accuracy rate in distinguishing lifeless space rocks from life-bearing samples using chemical data alone. Led by Amirali Aghazadeh, the research measures soluble organics using mass spectrometry and identifies molecular patterns. LifeTracer utilizes patterns in mass spectrometry data, effectively creating chemical fingerprints that aid in classifying samples as abiotic or biotic. Notably, it reveals useful biosignatures, enhancing the search for extraterrestrial life. The technology is poised for future planetary missions, assisting in the analysis of samples from potential past habitable environments, highlighting organic structures that signal life. This advancement promises a significant leap in understanding life’s origins, both on Earth and beyond.
Source link
Share
Read more