Unexpected Evidence of Life Found in 3.3-Billion-Year-Old Rocks Using AI
Life on Earth may have appeared far earlier than scientists believed, according to new chemical evidence preserved in rocks more than 3.3 billion years old. An international team led by the Carnegie Institution for Science found molecular signals suggesting that oxygen-producing photosynthesis emerged nearly a billion years earlier than previous records.
The findings, published in Proceedings of the National Academy of Sciences, rely on high-resolution chemistry paired with artificial intelligence to detect biological patterns long after their original molecules have vanished.
“Ancient rocks are full of interesting puzzles that tell us the story of life on Earth, but a few of the pieces are always missing,” said Katie Maloney, a co-author, in a press release. “Pairing chemical analysis and machine learning has revealed biological clues about ancient life that were previously invisible.”
Read More: First Evidence From Proto Earth May Be a Chemical Imbalance Hidden Inside Ancient Rocks
Why Early Life Is Hard to Detect
Early Earth was home to microbial mats and simple cells that rarely fossilized. Over billions of years, these materials were buried, heated, crushed, and fractured as Earth’s crust shifted. Those transformations all but erased the biosignatures that once held clues to the origins and early evolution of life. Because of this, scientists have traditionally only been able to identify reliable molecular traces in rocks younger than 1.7 billion years.
This has made it difficult to reconstruct Earth’s earliest biosphere and the timing of major events like the rise of photosynthesis.
The new study challenges that limit. It shows that even when original biomolecules have vanished, the pattern of molecular fragments preserved in ancient rocks can still carry information about whether life was once present.
Identifying Ancient Life Using AI
To uncover these patterns, the team analyzed organic and inorganic material from ancient rocks by breaking them down into molecular fragments. The machine-learning model was trained on more than 400 samples — including modern plants, animals, billion-year-old fossils, microbial mats, and meteorites — allowing it to detect the chemical fingerprints of life.
Among the samples were exceptionally well-preserved one-billion-year-old seaweed fossils from Yukon Territory, which helped the AI learn what early photosynthetic organisms look like in molecular form.
Once trained, the AI system distinguished biological from non-biological chemistry with over 90 percent accuracy. It also identified molecular signs of photosynthesis in rocks at least 2.5 billion years old, pushing chemical evidence of this process hundreds of millions of years earlier than previous work and showing that the distribution of degraded molecular fragments can still reveal whether life was once present.
“Ancient life leaves more than fossils; it leaves chemical echoes,” said Dr. Robert Hazen, a co-lead author of the study, in the press release. “Using machine learning, we can now reliably interpret these echoes for the first time.”
Searching for Life on Other Worlds
Altogether, the work offers a clearer view of Earth’s earliest biosphere and expands the tools available to study it. And because the method can detect biological chemistry even after billions of years of alteration, it may prove useful far beyond Earth. The same analytical approach could be applied to samples from Mars or other worlds to evaluate whether they ever supported life.
“This innovative technique helps us to read the deep-time fossil record in a new way,” Maloney said. “This could help guide the search for life on other planets.”
Read More: Earth Formed 4.54 Billion Years Ago – How Do Scientists Know?
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