Sony’s AI Patent Could Make PlayStation Bosses Learn How You Play
For the game genres that would be impacted, virtually any combat-centric single-player game could be enhanced by a system like this. The game itself doesn't need to have complex systems: the fundamentals of PVP play in the fighting game genre, for example, revolve around "footsies," or what players of other games would call "positioning" or "spacing." An ML AI model could be transformative for single-player games, even if its functions were as simple as controlling enemy spacing and attack timing.

That isn't to say this is completely good news. Sometimes, being able to "solve" a single-player game down to the minutiae of exact enemy behaviors is what makes a game fun and replayable. But then, many speedrunners also enjoy "randomizers" and other mods that exist explicitly to diminish the importance of memorization. Design-wise, a feature like the one outlined in the patent would certainly make a game more complex, but not necessarily "more fun".
If a complex single-player action or adventure game could be designed to learn how to counteract a player's strategy, however, the theoretical replay value of such a title could be near-infinite. A number of complex, niche subgenres of action games (Ninja Gaiden, Dark Souls, Devil May Cry, etc.) have already been played for decades without adaptable AI, though.
A machine learning model isn't actually needed to make adaptive enemies. In fighting games like Tekken 8 or Street Fighter 6, incredibly detailed player Ghosts learn common player behaviors and responses already. Single-player content in those and other games have also used features like input reading, where the enemy has perfect reflexes to everything you do because it knows as soon as the button is pressed.
Still, using machine learning to adapt and customize gameplay to a specific gamer's style and capabilities could spur some interesting innovations and make tomorrow's games even more realistic and immersive.