It's not just different interface, but different workflow.

In traditional ML you need to a) define model to do prediction A -> B b) train the model, which may take minutes c) then do the predictions form A -> B, which takes (1, 10, 100) microseconds

With predictive queries, you: a) Ask prediction for any X based on any A, B and C and expect answers in (1, 10, 100) milliseconds

You basically trade throughput and latency to get higher productivity, faster iteration and simplified overall sysstem