I have a smart RSS reader I am working on called YOShInOn. The main UI looks like TikTok or Stumbleupon, I can thumbs up, thumbs down or favorite articles, out of maybe 2000 articles a day it picks maybe 300 to show me, maybe I really read 200 on the average day.
Once the articles get favorited though there is the problem of navigating them, I just added some simple text search capability but there is a huge amount of room for improvement there. If it gets the ability to ingest articles via bookmarklet than it becomes a bookmark manager, add some ability to enter notes locally and it becomes a more general knowledge base manager.
It could really use "tags" but when it does these will be tags for the ML age, particularly it will be possible to have positive, negative and indeterminate tags. If the ML system thinks a tag applies it goes into indeterminate status and could be set to negative or positive to make it a training example.
Once the articles get favorited though there is the problem of navigating them, I just added some simple text search capability but there is a huge amount of room for improvement there. If it gets the ability to ingest articles via bookmarklet than it becomes a bookmark manager, add some ability to enter notes locally and it becomes a more general knowledge base manager.
It could really use "tags" but when it does these will be tags for the ML age, particularly it will be possible to have positive, negative and indeterminate tags. If the ML system thinks a tag applies it goes into indeterminate status and could be set to negative or positive to make it a training example.