Can you elaborate on that just a bit, I couldn't find anything relevant by doing a quick search for a few combinations of those keywords.

I'm not smart enough to go into the technical details, so I'll use an example instead.

Machine learning is very effective in categorizing things - for example, given an image estimate whether it pictures a cancer cell or not.

On the other hand, machine learning sucks where you need to predict things instead of categorizing - for example, given a set of factors, figure out your risk of getting cancer within 5 years.

Any such machine learning predictive system will be useless due to under- or overfitting.

(Again, I'm not an expert, just a guy who has many years of experience trying to build such predictive systems.)

They may mean machine-learning-assisted branch predictors. No clue otherwise.