Yeah, I’ve been noodling around that idea all week. Grab a Raspberry Pi or an Arduino with a cheap OLED, hook up a small board, and run a simple neural net in a loop. You can feed it its own moves as training data—basically let it play thousands of games against itself, tweak weights on the fly. The trick is balancing exploration and exploitation so it doesn’t get stuck in the same pattern. Think of it as a tiny sandbox where the engine is both teacher and student. If you want a quick prototype, start with a shallow neural net, maybe a few hidden layers, and let the reward be whether it wins or loses. That self‑reinforcement loop can surprisingly teach it basic opening theory and endgame tactics without any human games. Just keep the board cheap and the code lightweight, and you’ll see it start making moves that feel… oddly strategic.