[ellisv]

> Unfortunately, it turned out to be a chicken and egg problem. For the feature to work perfectly we needed a large amount of training data to train our models. But without the feature actually deployed, we didn't have any way to collect any training data.

Everyone outside of data science seems really surprised by this and I can't count the number of times someone has asked me to build an algorithm for X but has none of the data to support doing so. It doesn't mean the feature/product can't be built but they often want a supervised learning solution without the cost (and time) of acquiring the ground truth data.