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Above note is the reason Google can't recommend you anything. Consider momentarily the amount of data processing necessary to somehow recommend a relevant vide

by araes 2y ago

Above note is the reason Google can't recommend you anything. Consider momentarily the amount of data processing necessary to somehow recommend a relevant video from: ~14,000,000,000 videos on Youtube 615 seconds (~10 minutes) mean length. Which works out to: 8,610,000,000,000 seconds 143,500,000,000 minutes 2,391,666,666 hours 3,274,083 months 272,840 years 27,284 decades 2,728 centuries 273 millennia 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 https://news.ycombinator.com/item?id=39421041 [2] "What We Discovered on ‘Deep YouTube’", https://www.theatlantic.com/technology/archive/2024/01/how-m 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 https://journalqd.org/article/view/4066/3766

mustyoshi 2y ago
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.
- jmb99 2y ago
  I think that “just” might be doing some heavy lifting in that assertion.
- sulam 2y ago
  Sure and classifying video is one of the classically hard things for computers to do. Really classifying in general.
spencerchubb 2y ago
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
Dylan16807 2y ago
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.

by araes 2y ago

mustyoshi 2y ago

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.

jmb99 2y ago
I think that “just” might be doing some heavy lifting in that assertion.
sulam 2y ago
Sure and classifying video is one of the classically hard things for computers to do. Really classifying in general.

spencerchubb 2y ago

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

Dylan16807 2y ago

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.