It's a fair question, but from my heydays doing ML research even good libraries can be pretty revolutionary. The engineering-side of ML is still in relative infancy.

For a great example look at all the papers Andrew McCallum's group has been able to publish by building on top of FACTORIE: they get to focus their time on the problem at hand rather than all the math required to solve it. Basically they can write code that generates a model dynamically but the framework handles all the inference. Compare that to how these things are built without such a framework: you spend most of your time painstakingly hand-deriving update rules and then implementing them as code.

IMHO, the exciting thing is that ML is getting closer and closer to being an everyday tool for engineers rather than something that requires you to be a full-time math person to use effectively.