This is a groundbreaking shit, and it's not about checkerboards or lizards. The Navier-Stokes differential equation governing fluid motion is an update rule that predicts the next state of any given point given its neighborhood and a few previous states. The key insight is that all the complexity of the fluid and air motion, the formation of clouds and the motion of flames, is governed by a simple law, by an equation that's uniformly and simultaneously applied to each point in space and all it needs is the immediate neighborhood of that point and its immediate history. Discovering this equation by looking at real-life samples is what's called science. It should be possible in principle to apply this DLCA model to a video recording of smoke, constrained to a thin 2D layer for simplicity, and let this model derive the Navier-Stokes equation. When you take this one step further and consider that the update rule itself may be changing according to another update rule, we'll get into some interesting territory. This might be why in our brain neurons are connected to a neighborhood of thousand neurons instead of just ten or so.
Following the tradition, Google execs are going to dismiss this discovery as irrelevant to the ads business, and a couple years later when DLCA will have turned the world upside down, they'll try to take credit saying it's their employees who have made the discovery.