A new approach to ground motion models (GMMs) is making waves in the field of seismic risk mitigation and infrastructure design. By integrating inherently interpretable machine learning techniques with physics constraints, researchers are addressing the opacity of traditional 'black box' models. This innovation is crucial as it enhances the reliability of engineering decisions, especially in the face of imbalanced seismic datasets that often lack sufficient large-magnitude records. This development not only boosts confidence in seismic assessments but also paves the way for safer infrastructure.