AI is helping seismologists find the next monster earthquake

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In 2017 Ross had an epiphany. He saw machine learning programs handle huge sets of photos-identifying and categorizing elements within them, and with accuracy and speed that humans couldn't match. So, he thought, why not apply a similar approach to seismology?

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Ross and his colleagues took seismic waveforms from across Southern California that human scientists had identified as genuine quakes. Then he made templates of them, snapshots of each earthquake's seismic wave pattern. Finally, he set an algorithm upon the seismic record, one searching for elusive quakes that matched those templates, those snapshots.

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There was a drawback, however. This program, a sort of precursor to true AI software, could only find earthquakes in the seismic record that it was taught to recognize. Novel seismic events went unnoticed.

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So Ross turned to more advanced tools: self-learning programs, software that could take preexisting information and make predictions about the future-in this case, what a vastly wider variety of earthquakes might sound like. Very quickly, these programs found all sorts of unfamiliar-sounding quakes-later verified by human scientists. "You just see so many things that were completely missed," Ross says.