indeed redundancy is fairly important (although the largest part, the training data, actually doesn't matter if chunks are missing).

But the type of consistency they were talking about is strong ordering - the type of thing you might want on a database with lots of people reading and writing tiny bits of data, potentially the same bits of data, and you need to make sure a users writes are rejected if impossible to fulfil, and reads never return an impossible intermediate state. That isn't needed for machine learning.