In a Kauffman NK network, N binary nodes each update via a random Boolean function of K inputs. With K=1, the network freezes; K=2 is the "edge of chaos" — attractors are short and stable; K≥3 leads to chaotic dynamics. This model captures gene regulatory network behavior: K≈2 matches biological robustness observations.