Say you want to swap out your embedding models, for instance from ADA to Titan. Are these embedding models comparable? How do similarity score ranges compare? Where to put a threshold for minimum match when doing retrieval? Or more from a research point of view how can we relate and fundamentally understand these embedding spaces better? This is what we aim to solve with Synthetic Query Probing, a fancy name for essentially (and intentionally) a very simple approach: embedding spaces are not d...