[syllogism]

I see how that came across as obnoxious, so thanks for the perspective.

I do think there's a pretty common failure mode for teams who don't have much experience with ML, though. Teams who don't have much experience with ML often take "We don't have much data" as a parameter of their problem, and don't see that this is something they can decide to change. This can lead to a lot of time spent experimenting with different unsupervised approaches that are a poor fit for what they're trying to do.