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Researchers have developed an AI-powered app called DinoTracker that can identify dinosaur species from fossilized footprints. The system achieves classification accuracy comparable to human experts, offering a novel approach to paleontological research.
AI 生成摘要
研究人員開發了一款名為DinoTracker的AI應用程式，能夠從化石足跡中識別恐龍物種。該系統的分類準確度可與人類專家媲美，為古生物學研究提供了新穎的方法。
Researchers say artificial intelligence system matches human expert classification about 90% of the time
Experts have created an app that uses artificial intelligence to identify dinosaurs from the footprints left behind after they stomped across the land tens of millions of years ago.
“When we find a dinosaur footprint, we try to do the Cinderella thing and find the foot that matches the slipper,” said Prof Steve Brusatte, a co-author of the work, from the University of Edinburgh. “But it’s not so simple, because the shape of a dinosaur footprint depends not only on the shape of the dinosaur’s foot but also the type of sand or mud it was walking through, and the motion of its foot.”
Writing in the Proceedings of the National Academy of Sciences, Brusatte and colleagues report how previous AI systems based their learning on footprints that had already been labelled as having been made by particular types of dinosaur. But, the team note, if those identifications are incorrect then the AI system will also be flawed.
“You never find a footprint and alongside [it] the dinosaur that had made this footprint,” said Dr Gregor Hartmann, the first author of the new research from Helmholtz-Zentrum in Germany. “So, no offence to palaeontologists and such, but most likely some of these labels are wrong.”
Taking a different approach, Brusatte, Hartmann and colleagues fed their AI system with 2,000 unlabelled footprint silhouettes. The system then determined how similar or different the imprints were from each other by analysing a range of features it identified as meaningful.
The researchers discovered these eight features reflected variations in the imprints’ shapes, such as the spread of the toes, amount of ground contact and heel position.
The team have turned the system into a free app called DinoTracker that allows users to upload the silhouette of a footprint, explore the seven other footprints most similar to it and manipulate the footprint to see how varying the eight features can affect which other footprints are deemed most similar.
Hartmann said that at present experts had to double check if factors such as the material the footprints were made in, and their age, matched the scientific hypothesis, but the system clustered prints with those expected from classifications made by human experts about 90% of the time.
Among other results, the team said the AI system supported what palaeontologists had previously noticed: that a set of footprints from the Triassic and early Jurassic are remarkably birdlike despite being about 60m years older than the oldest bird skeletons, the fossilised bones of Archaeopteryx.
Brusatte said this showed that the similarities were not just down to wishful thinking. “If these tracks were made by birds, that would mean that birds have a much older, much deeper ancestry than we used to think. And not just a few million years but tens of millions of years,” he said.
However, it is far from case closed. “I suspect it is more likely that these tracks were made by meat-eating dinosaurs with very birdlike feet – maybe bird ancestors, but not true birds,” Brusatte said.
Dr Jens Lallensack, of Humboldt University of Berlin, who has also used AI to help identify dinosaur tracks but was not involved in the study, said a key limitation was that the features of interest identified by the new system were not necessarily based on the shape of the foot itself.
He added that the birdlike tracks may be a result of the way the foot of a regular theropod sank into soft ground. “They are not evidence for an early appearance of birds,” he said.