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
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