@ The Chinese University of Hong Kong
Inspired by wave-like information propagation in nature, we view intelligence as a dynamic process evolving across space and time. Our work connects AI for Science, using AI to model and accelerate scientific discovery, with Science for AI, where insights from physics and dynamical systems guide the design of intelligent models.
Latest articles from the blog
We step outside the usual analytical framework and build a minimal dynamical model directly in representation space, abstracting away the details of network architecture and parameters.
A physicist’s view of K-Flow, from continuity equations and Hamiltonian transport to renormalization-group-inspired scale evolution.
Why is energy the essence of generation? We introduce K-Flow, a generative framework that aligns the flow path with the frequency and energy of the data by modeling in the K-amplitude space.