If you train it on multiple games then you could produce new games that have never existed before, in the same way image generation models can produce new images that have never existed before.
It's unlikely that such a procedurally generated mashup would be perfectly coherent, stable and most importantly fun right out of the gate, so you would need some way to reach into the guts of the generated game and refine it. If properties as simple as "how much health this enemy type has" are scattered across an enormous inscrutable neural network, and may not even have a single consistent definition in all contexts, that's going to be quite a challenge. Nevermind if the game just catastrophically implodes and you have to "debug" the model.
