It's an n-gram model so it can easily have as many parameters as you want to store. Skimming it, I think the '8 trillion parameters' here means '8 trillion trai

It's an n-gram model so it can easily have as many parameters as you want to store. Skimming it, I think the '8 trillion parameters' here means '8 trillion trainable n-gram parameters but it's very sparse and most of them are simply defined by omission to be a small constant like epsilon due to not being represented in the training data at all and so suffering from the 0-count problem'. (Old problem - even Turing and Good spent a lot of time discussing how to handle 0s in contingency tables because that happens a lot in cryptography!)