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YouTube has different needs for different videos. The average barely-viewed video can use quick and dirty hardware compression, but a large fraction of views are on a small fraction of videos, which is the sort of thing that more intense AI-assisted optimization would help with.


Id bet the median YouTube view count is zero, in which case the real gains would be from accurate inference of which videos fell into that class.


In that case, they could probably just trigger a re-encoding of videos when they cross into 100+ views from over 50 unique IP addresses or something like that.


LOL. I never thought about it before, but that statistic would be interesting to know. How close to zero is it?




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