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You need to have enough high quality data to train with, knowledge how to do it, and developer time.

In practice, that's enough of a barrier to not even try the approach on a number of cases where it might potentially be useful.

I wouldn't be surprised if Jev turned out to be a "gateway drug" that validates approach on a use case, the team gathers experience and labeled data, and switches to an in house locally tuned model to minimize costs.



Exactly. And that labeled data could be collected by just recording what they feed jev and what the decision is.




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