True in the ideal case, but taken together (e.g. corpus retraining, temperature settings, slight input changes, initial descent parameters) unpredictability and indeterminism become difficult to distinguish. Especially in the distributed training case, training data may be propagated to different nodes in different order (e.g. when leaving it to a query optimiser), which makes any large-scale training operation difficult to reproduce exactly.