Toward intellidynamics: A path from HH² to modern AI

Understanding intelligence requires understanding the complexity emergent from dynamics. From the Hodgkin-Huxley model of single-neuron behavior to Hopfield-Hinton high-dimensional neural networks, and now to transformers and reservoir computing, intelligence arises from the interplay of complex dynamical systems. Collective computation, attractor dynamics, and emergent phenomena demonstrate that system-level behaviors transcend individual components. Advances in artificial intelligence reveal that high-dimensional parameter spaces, nonlinear interactions, and memory effects shape capabilities interpretable through dynamical systems theory. This emerging frontier, which we term Intellidynamics, unites mathematical modeling, computational architectures, and experimental insight to illuminate how intelligence arises, adapts, and interacts with the principles of complex systems, enabling approaches that leverage mutual benefits between modern AI and complex dynamics.