Modeling software reveals patterns in continuous seismic waveforms during series of stick-slip, magnitude-5 earthquakes

A team at Los Alamos National Laboratory has used machine learning—an application of artificial intelligence—to detect the hidden signals that precede an earthquake. The findings at the Kīlauea volcano in Hawaii are part of a years-long research effort pioneered at Los Alamos, and this latest study represents the first time scientists were able to detect these warning signals in a stick-slip fault, the kind that can generate massive destruction.