Matrix spillover quantification measures a crucial challenge in deep learning. AI-driven approaches offer a novel solution by leveraging powerful algorithms to assess the extent of spillover effects between separate matrix elements. This process boosts our knowledge of how information propagates within mathematical networks, leading to better model