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The secret is how it chooses videos to recommend, not the tech stack it uses and how fast it is


I would assume it's time spent on video and they start to build a profile of which users like what kind of content. X liked video 934934 so Y probably also likes that kind of video. Group people in buckets.


I'm sure this is part of it, but I suspect it goes deeper than that. I'd guess they probably have some kind automated categorisation algorithm that can extract features from the videos




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