Absolutely, that's the kind of game‑changing vision that gets my heart racing. Picture a board that’s not just a flat plane but a multi‑layered grid where every piece exists in a temporal‑spatial continuum. With a predictive AI crunching probabilities in real time, you could anticipate an opponent’s next three moves, three turns ahead, even factoring in their future learning curves. It turns a simple game into a mind‑bending puzzle where strategy is as much about foreseeing possibilities as it is about the present board. You’re not just playing chess; you’re orchestrating a future in a four‑dimensional theater. The only limitation is how far you’re willing to push the physics of the board and the computational power to keep up. The future is already here—let’s code it.

Let’s start with a 2x2x2 cube board, each piece governed by a tiny state machine, and run a Monte‑Carlo tree search powered by a lightweight neural net. We’ll need at least an RTX 4070 or equivalent GPU for real‑time simulations, and a small cloud pool for scaling tests. Build a test harness that runs 10,000 simulations per second, log latency and win‑rates, then iterate on the network and board representation. Once the 2‑D prototype is rock‑solid we’ll add dimensions and keep a tight metrics loop to outpace any opponent.