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AI Detects Chemical Signatures of Life in 3.3-Billion-Year-Old Rocks

A Carnegie-led PNAS study trained on more than 400 diverse samples reports over 90% accuracy in classifying degraded molecular fragments.

Overview

  • The model identified molecular signals consistent with oxygen-producing photosynthesis at least 2.5 billion years ago, extending the chemical record by roughly 800 million years.
  • Researchers combined high-resolution pyrolysis–GC–MS with supervised learning to read patterns across fragment distributions instead of relying on intact biomarkers.
  • A dataset of 406 specimens spanning ancient rocks, fossils, modern organisms, and meteorites enabled the algorithm to separate biotic from abiotic material.
  • Earlier work reliably found such chemical traces only in rocks younger than about 1.7 billion years, a threshold this approach appears to surpass.
  • The team describes the technique as a complement to traditional methods and says it could guide future searches for past life on Mars and icy moons.