
AI Uncovers Hidden Slow-Slip Signals Along the San Andreas Fault
Researchers trained machine-learning tools on eight years of borehole strain data along California’s San Andreas Fault near Parkfield, identifying slow-slip events that often coincide with nearby low-frequency earthquakes, suggesting slow slipping contributes to fault stress and could inform future earthquake forecasting efforts.













