If the training that did not use synthetic data failed to capture some aspect of the information contained, then using data synthesized from the original data could help to capture it, thus it could result in the models getting better.

But that is because the synthetic data helped the model capture what was already there in the training data.

But after all such information has been extracted, then it would not be possible to use synthetic data or anything that is derived from the original data to create "new" information for training....