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Weirdly it seems to be because of scale - YouTube is just so big with such a high volume of videos, user data, and new videos, they can't yet run the ML algorithms they'd really want to over the whole corpus.

https://www.quora.com/How-does-YouTubes-recommendation-algor...

So meanwhile we get emotionally-stunted video recommendations from a savant toddler. It's really harmful.



That just sounds like a poor choice of a first step; why not use a random sample, then apply their sophisticated algorithm on that?




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