An early version of Alphago was trained on expert human games and did go on to defeat the human champion. Later versions of Alphago are stronger still and developed entirely through selfplay to become superhuman. I would say these versions did exceed their training data because they started training on basically random games and got increasingly better as they learned. What is that if not exceeding what they started from?

Alphago is proof that ML systems can exceed human abilities in at least some domains. Other domains, like identifying animal breeds/species by sight, I believe ML models are also super human. It's just not correct to say models are limited by their training data to something less than human quality. We have multiple counterexamples already.