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Some great points made. In my experience, screwups tend to start when - the "prototype" / minimum viable product can't scale. N^2 algorithms have a cost -- and it can be high! - the data source is not-repeatable/updating/lacking lineage





Yeah, so many models made from a data source that is a .csv that someone updates manually twice a year, no way to put that to production