Matrix spillover quantification measures a crucial challenge in deep learning. AI-driven approaches offer a promising solution by leveraging sophisticated algorithms to interpret the level of spillover effects between different matrix elements. This process boosts our knowledge of how information transmits within neural networks, leading to improve