Matrix spillover quantification represents a crucial challenge in complex learning. AI-driven approaches offer a novel solution by leveraging cutting-edge algorithms to interpret the level of spillover effects between different matrix elements. This process improves our knowledge of how information flows within neural networks, leading to more mode