Abstract
Artificial intelligence (AI) has accelerated scientific prediction and design, but accurate predictions and promising structures alone do not explain how scientific systems behave. Using molecular science as our primary lens, we envision a progression from property prediction through structure generation toward a new paradigm coined Wave Intelligence. It integrates complementary modalities into a shared latent space and learns how those representations evolve under changing conditions. The term "Wave'" evokes the dynamic, evolving nature of scientific processes. This paper further outlines the research challenges and evaluation principles for developing Wave Intelligence and assessing its contribution to mechanistic understanding.