I am now imagining a (probably short) story in which the AI does learn to predict players perfectly, even the creative ones, and ends with a gamer taking his hands off the controller and allowing the AI to play exactly as he would have and wondering what was ever the point.
I think prediction failures are more likely to punish the opponents of the unpredictable guy. In a lot of online shooters, people with 300ms+ ping blink around unpredictably and appear to suddenly murder you out of nowhere, but they don't seem to have any trouble themselves.
None taken. But your claim is that creativity is not possible anymore, since it was all done in the "millions of hours of game state". However, if creativity is possible, then my argument is correct.
Another issue is that machine learning/AI don't predict rare events, like earth quakes. So even with all the knowledge in the world, it won't predict a rare creative move of a player.
But every event, creative or otherwise, is made up of hundreds of smaller events. That complicated wall jump - 360 kill you just did used several input signals. Even if the server side AI can't predict the exact final outcome, it can definitely help with the intermediate, well known states for at least some of the input systems.
I say some but I do believe a large enough volume of data can improve the performance of this class of input/states.
Yes, and then you predict something, broadcast it to your clients, and it ends up being wrong so the clients have to roll back. Would not be a good experience.
Stadia could sell it as an add-on to players which not only don't want to play their games themselves, but also aren't satisfied by watching other people play through their games on YouTube or Twitch. With this add-on, they can finally watch themselves play through their games, without having to lift a finger to, you know, actually play!
Black market dealers would swap Terabytes of hot RAM with manually inputted data from the best e-sport players in the world. Corporate enforcers would hack those dealers to delete the data.
I thought about it. But first, you need a lot of information to train a model, so it would only work for very heavy players. Second, creativity is not defined only as doing an action that others didn't do (often or never) before, but also of doing an action that you didn't do (often or never) before.
The problem there seems two fold, one that you need even more beefy hardware to predict, simulate and render ahead of the player input particularly when it has to catch up to deal with misprediction and secondly that mispredictions are going to make the game feel really imprecise at best and jarring at worst.
I'm also skeptical about the ability for a model to generate predictions without having too many mispredictions to make it viable.
I think the problem here is, the game is made by Studio A, but it's run by Google in the cloud. Studio A probably doesn't have enough of an incentive to put this in the binary, but Google doesn't have the source, so they can't change the game loop.
In a twitch shooter, you mouse over a visible opponent. Would the AI be more likely to pre-emptively pull the trigger for you? Or more likely delay and swing the aim passed the opponent before shooting at air? AKA Is the training set for predictive user actions based on experience of players better or worse at the game than you?
True, that could work, and the two frames are probably very similar, so wouldn't even require that much more bandwidth. As someone here pointed out, however, the game controller is connected to the cloud directly, so the display doesn't even know of the inputs until the roundtrip is already done.