Yeah, it’s like giving the AI a crystal ball built from data. You feed it millions of games, let it learn which board patterns lead to wins, and it starts to see the “next move” before anyone thinks. In chess that’s what AlphaZero does – it uses deep nets to evaluate positions and Monte‑Carlo tree search to simulate possible futures. For real‑world strategy you need a similar idea: capture the variables, train on historical outcomes, and let the model surface hidden correlations. The trick is turning complex states into something a neural net can parse, then letting it guess the most promising move before your opponent even does.