Netflix simply attempting to provide somewhat relevant recommendations was a massive data crunching effort years ago, and even that was "only" the official movies and television of humanity. Data take from a previous post I made 9 months ago [1] and from this article [2] and this paper on Youtube data statistics [3].
Underrated reason for tiktok's success: shorter videos lend themselves way better to recommendation algorithms, because you have better data about what users want to see
Almost all my recommended videos have tens of thousands of views or more. I don't know for sure if the algorithm usually ignores 97% of videos, but it might as well be doing that. Doing that vastly reduces the number of options and means you have lots and lots of data for each video.
It can't be that hard, once you develop a profile for a user, you just need to classify the incoming videos and cross reference their profile against the classifications.
Consider momentarily the amount of data processing necessary to somehow recommend a relevant video from:
Which works out to: Netflix simply attempting to provide somewhat relevant recommendations was a massive data crunching effort years ago, and even that was "only" the official movies and television of humanity. Data take from a previous post I made 9 months ago [1] and from this article [2] and this paper on Youtube data statistics [3].[1] https://news.ycombinator.com/item?id=39421041
[2] "What We Discovered on ‘Deep YouTube’", https://www.theatlantic.com/technology/archive/2024/01/how-m...
[3] "Dialing for Videos: A Random Sample of YouTube", https://journalqd.org/article/view/4066/3766