Which is sad, because even multiplayer would be very interesting with Alien style opponents who were actually clever and cooperated and had memories stretching over the timespan of the games existance. (Years.)

I think there's more to it than time constraints. Of course the efficiency of the method is a big concern, but we also have to remember that games are primarily experiences. In a lot of the games I play, stuff like stealth games, rougue-lites, and DotA, the simple and predictable behavior the current models is required for the game to work. The models HAVE to be stupid to make the game work.

Another thing worth noting is that "smart" game AI is as much about presentation as it is about actual intelligence. That is, if your NPC's are super smart, but doesn't communicate their smart decisions to the player, they will often still be perceived as dumb. That's why "barks" are such a big thing in games: NPC's tell each other what they saw or what they're doing to communicate to the player that they made a potentially smart decision. This communication may not be so simple with a machine learning based AI where the intent of the NPC isn't known.

Similarly, often super intelligent AI doesn't look very intelligent, doesn't feel very intelligent or is just not very fun to play against.

It also depends on the type of game. If the player spends a lot of time observing NPC's (eg in a stealth game), then intelligent AI is more important than if the expected lifetime of the NPC before the player slaughters them is only a few seconds (eg in a shooter).

I don't think its necessarily time constraints. Its also understanding the AI: why did the NPC make the decision it did? Exlpainable machine learning is still very much a research topic. Its about giving the designer the ability to control and author the interactions that the player will get. Its about controlling what situations are actually desired (there was a story about the AI in The Elder Scrolls: Oblivion's "Radient AI" system where they had to tone the NPC's autonomy down because they found that NPC's would tend to do unfun things like murder everyone in town). In terms of training machine learning models, for many games you may simply have no way of gathering sufficient quantities of data to train it to do the behaviours you want for the scenarios where you want them. Time may not necessarily solve these, or at least you'd need a decade to do everything.

Personally, I like sandbox RPG's, so I personally want to see better NPC AI and deeper NPC simulations. I want to see NPC's go about their lives independently of the players interactions and have their own agency in the world. So I'm very much interested in seeing better decision making, planning and simulation of characters in games. But machine learning based techniques aren't necessarily the answer, if you want the game to still be a game and be fun for the player.