According to God of Prompt, Grassmann manifolds are gaining attention in AI architecture design due to their finite-dimensional explicit algebraic structure, governed by Plücker relations. As reported by God of Prompt, these manifolds naturally capture local linear geometry, enabling computation of global invariants and providing a mathematically traceable framework. Unlike complex tensor spaces, Grassmann manifolds offer a structure that can be rigorously analyzed, presenting new opportunities for geometric interpretability and robust model analysis in machine learning.