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I would like to see more than just toy benchmarks. Also, can you provide any information on theoretical basis of this?

I can see this carving out a space for low value tasks.




We have few customers in production. One is about smart purchase invoice automation and - IMO - the real world data set is not that different from those StatLog / UCI / Kaggle datasets.

Of course our customer datasets tend to be on the easier side of the ML application field, but like you mentioned: the easy / fast or the low / mid-value ML applications are the place, where Aito / predictive database strengths play out and where they can carve out space.




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