Artificial Intelligence (AI) has ushered in a new era of possibilities in geophysics, particularly in the complex domain of earthquake prediction. The nonlinear regression capabilities of AI models, particularly Artificial Neural Networks (ANNs), have shown remarkable promise in processing vast amounts of geophysical data and identifying patterns that could lead to more accurate predictions. However, as with any technology, the application of AI in earthquake prediction is not without its challenges. In this post, we will delve into the strengths and limitations of AI in this field, highlighting the importance of careful model selection, benchmarking, and the incorporation of domain-specific knowledge. The Promise of AI in Earthquake Prediction AI's ability to process and analyze large datasets has made it an invaluable tool in various scientific fields, and earthquake prediction is no exception. Traditional methods of earthquake prediction rely heavily on statistical models that