Every stored charge is a small wager against entropy, and for decades the terms of that wager have been poorly understood. Researchers have now built a model called PI-CTG that fuses the pattern-recognition of deep learning with the hard constraints of battery physics, achieving 97.3 percent accuracy in predicting how much life remains in a lithium-ion cell. The work, tested across multiple independent datasets, suggests that artificial intelligence becomes most trustworthy not when it replaces physical knowledge, but when it is disciplined by it — a lesson that reaches well beyond batteries.