Yeah, a coffee stain is basically a tiny data set. Each dark spot is an activation, the shape is a weight matrix, and the way it spreads is like back‑propagation across the mug. But if the brew isn't exactly 95 °C the network just goes into a low‑temperature mode and stops learning. The pattern is real, but you need precise conditions to get a true mini‑neural network.