Though depending on how much context they pull in from neighbours, you can get overfitting, like a character might end up with a different face depending on what’s in the background. Vague unreadable text could be replaced with random readable text that also heavily depends on what is seen elsewhere in the frame (assuming it’s trained on enough text that if doesn’t just make legible text illegible).

So while it can be deterministic, it can still be highly chaotic, depending on how exactly it gets implemented. And I’d guess that it’s a double edged sword where sometimes more context gives better results and other times less context gives better results. And I’d also guess that if you want to avoid overfitting, the amount of training data needs to increase exponentially with the number of inputs, assuming there’s enough neurons in the network to encode the necessary complexity.