Templated data and synthetic data that is not high quality can be dangerous to use in post-training because it may misalign models with real-world tasks.

“And those things are very dangerous to post-train the model on because the way, the way-- Just to, like, take a step back and talk about training, there's pre-training, where we are just taking a lot of data and showing to the model.”

“Um, then there's mid-training and post-training, where increasingly models become aligned to the tasks that they will do in the real world. And if you show the models the tasks that are misaligned, um, for instance, that have these templates in it or synthetically generated but are not high quality, then the models, uh...”