The University of Texas has developed an AI model that accurately predicted 70% of earthquakes during a seven-month trial period in China, helping to prevent disasters.

Recent advancements in artificial intelligence (AI) have shown great potential for improving the precision of earthquake predictions, an area that has historically been difficult to master. Researchers have developed AI models capable of accurately predicting the location and magnitude of earthquakes, achieving 70% accuracy in recent tests. These models not only forecast earthquakes but also evaluate aftershocks and the intensity of seismic events, which is crucial for disaster planning and response. In the Arabian Peninsula, a hybrid AI approach has proven more effective than traditional methods, highlighting its ability to manage large data volumes and improve forecasts in critical areas. While these models still require further validation, recent advancements suggest that earthquake prediction could become more feasible in the near future.

These AI developments are not limited to earthquake prediction but are also being used to predict aftershocks and assess their intensity, which is crucial for disaster planning and response. Although there is still much to improve, especially in the global application of these models, recent advancements indicate that earthquake prediction, once considered an insurmountable problem, could become more viable than previously thought.