According to God of Prompt, aggressive pruning in neural networks can lead to subnetwork collapse, where specialized subnetworks begin to overlap and overall performance declines. The innovative aspect is that mask similarity can predict this collapse before any drop in accuracy occurs, serving as a label-free early warning system for maintaining neural network integrity and performance. As reported by God of Prompt on Twitter, this approach offers significant potential for optimizing neural network pruning strategies in AI model development.