3 ms·

Well just for me I don't care what's trending so don't need the feed of other people's views. But absolutely needing a feed of new posts might be problem.

creato 6y ago
That's really missing the point. Recommendation engines are a lot more dumb than you are thinking. They don't understand the content at all. They only know that thousands of users that watched the same videos as you in the past also watched this other new video, so you might like it as well. A recommendation engine that works solely based on your own watch history would require a totally different approach using algorithms that are years/decades/forever away from existing.
- imglorp 6y ago
  Good points. It does make sense that the job is simpler with everyone's history and inputs, if you can keep PII out of it. Are there any good references on recommendation aggregation algorithms? Here's a simple proposal that keeps everyone's stuff anonymous and allows a rec service to pay bills. Distribute the pool of everyone's watch histories/prefs/etc using IPFS, which is a DHT with static names and some storage. User clients put the share data into IPFS and register into a public pool. The client remembers their own hash. Rec services (there can be multiple) pull everyone's sets periodically and aggregate/indexe them. Users can then retrieve a batch of new recs by sending a small fee to the service of their choice along with their hash and the server will place some new recs into their bucket. If the recs are not suitable, they can try another service.
  - halflings 6y ago
    If I send you links to 2-3 rare videos and you view them, I can probably uniquely identify you (or restrict the list of potential users to ~5 users then recognize you based on other videos you would have watched). I then have access to your full video watching history. Even without this, I could just check videos you shared on Twitter, follow the same process, and have a decent chance of identifying you. Anonymization is very very hard. Maybe federated learning is more promising here, keeping all your data privately stored on your own devices.
- halflings 6y ago
  > That's really missing the point. Recommendation engines are a lot more dumb than you are thinking. They don't understand the content at all. I think you're the one underestimating modern recommender systems, especially the ones built by advanced teams in big tech companies. They absolutely use content features. Among other advantages, this counters the cold start problem (how will you learn about a new video if it doesn't get recommended to anyone).
aasasd 6y ago
Have you ever seen the torrent of garbage that is new posts on e.g. Reddit or Imgur? You only see decent posts on the ‘front page’ because some people sift through that and filter out teenagers' low-effort attempts. YouTube has hours of video uploaded every minute. A non-centralized, context-less recommendation system would mean that you are offered those crap videos together with ones that are the standard for ‘good’ now. Just get into the long tail on any search results and see if you want those. A non-monopolized video discovery would be splendid, only who knows how to achieve that. Perhaps it would be more realistic to do the recommendations based on the numbers of ‘retweets’ in federated networks—in a more ‘social’ style instead of views (dunno if PeerTube already offers that). Also, an open system will be incessantly gamed.

creato 6y ago

That's really missing the point. Recommendation engines are a lot more dumb than you are thinking. They don't understand the content at all. They only know that thousands of users that watched the same videos as you in the past also watched this other new video, so you might like it as well. A recommendation engine that works solely based on your own watch history would require a totally different approach using algorithms that are years/decades/forever away from existing.

imglorp 6y ago
Good points. It does make sense that the job is simpler with everyone's history and inputs, if you can keep PII out of it. Are there any good references on recommendation aggregation algorithms? Here's a simple proposal that keeps everyone's stuff anonymous and allows a rec service to pay bills. Distribute the pool of everyone's watch histories/prefs/etc using IPFS, which is a DHT with static names and some storage. User clients put the share data into IPFS and register into a public pool. The client remembers their own hash. Rec services (there can be multiple) pull everyone's sets periodically and aggregate/indexe them. Users can then retrieve a batch of new recs by sending a small fee to the service of their choice along with their hash and the server will place some new recs into their bucket. If the recs are not suitable, they can try another service.
- halflings 6y ago
  If I send you links to 2-3 rare videos and you view them, I can probably uniquely identify you (or restrict the list of potential users to ~5 users then recognize you based on other videos you would have watched). I then have access to your full video watching history. Even without this, I could just check videos you shared on Twitter, follow the same process, and have a decent chance of identifying you. Anonymization is very very hard. Maybe federated learning is more promising here, keeping all your data privately stored on your own devices.
halflings 6y ago
> That's really missing the point. Recommendation engines are a lot more dumb than you are thinking. They don't understand the content at all. I think you're the one underestimating modern recommender systems, especially the ones built by advanced teams in big tech companies. They absolutely use content features. Among other advantages, this counters the cold start problem (how will you learn about a new video if it doesn't get recommended to anyone).

aasasd 6y ago

Have you ever seen the torrent of garbage that is new posts on e.g. Reddit or Imgur? You only see decent posts on the ‘front page’ because some people sift through that and filter out teenagers' low-effort attempts. YouTube has hours of video uploaded every minute. A non-centralized, context-less recommendation system would mean that you are offered those crap videos together with ones that are the standard for ‘good’ now. Just get into the long tail on any search results and see if you want those. A non-monopolized video discovery would be splendid, only who knows how to achieve that. Perhaps it would be more realistic to do the recommendations based on the numbers of ‘retweets’ in federated networks—in a more ‘social’ style instead of views (dunno if PeerTube already offers that). Also, an open system will be incessantly gamed.