Spatiotemporal Evolution with Attractor Dynamics
Following von Neumann's vision of cellular automata — exploring computation as a physical process.
Three physics-inspired postulates — locality, symmetry, and stability — derive the SEAD architecture (neural cellular automaton). Validates on parity (perfect length generalization), addition (L=16 → L=1,000,000 at 100%), and Rule 110.
Long-range dependency in multiplication is a mirage of computational spacetime. A 321-parameter neural cellular automaton on a 2D outer-product grid achieves 683× length generalization. Includes an interactive browser demo.
Paper + Demo · arXiv · Code
An 18,658-parameter 2D neural cellular automaton, trained with 1-bit boundary supervision on arithmetic expressions, spontaneously develops internal structure aligned with the CKY parsing algorithm (Pearson r ≈ 0.71). Includes an interactive browser demo.
Paper + Demo · arXiv · Code