neural cellular automata

Adam Hibble ✓ @Algomancer · 12h Can we train a family of local differentiable physical laws such that persistent local structures emerge which contain compressed predictive models of their own future environment and exhibit measurable causal control over that environment? Idk, but i thought it was an interesting question if you try to take it seriously. First attempt It's pretty at least. A ~100M-parameter a local energy-conserving Hamiltonian field theory. its local rule is the symplectic leapfrog of a learned Hamiltonian. continuous, second-order, reversible, energy-conserving. Can kinda think of it as a second order in time neural ca, optimised such that cell states causally predict future local state whilst maximising variance, symplectic so it can't just push magnitude. [Embedded video/animation, paused, showing four panels: "field φ[0:3]", "energy density", "momentum |π|", "field φ[3:6]" — colorful abstract turbulent-looking field visualizations. Overlay text: "large step 76500 E=4046492 drift=0.305 CV=1.24". Playback control shows 0:03.]