1. Any video using sentimental music (usually piano) to explain a story (helping someone etc, rescuing and a dog and shit).
2. Need someone to model those video with cadences where someone talks like a YouTuber, you know when their voice cuts right into the next sentence, sort of like removing frames from an action movie. They are getting to sound like that TV reporter archetype.
3. Identify the ‘please please like and subscribe’
4. Can we model the live ad reads and catch those?
I honestly don’t know anything about ML but I’ll literally sit through anyone’s Coursera (Will pay $$$) if you just walk through the concepts and how things like this can be tackled.
In other words, I’m suggesting the future of spam and ad blocking has to occur on this level, because there’s no other way.
> SponsorBlock is an open-source crowdsourced browser extension and open API for skipping sponsor segments in YouTube videos. Users submit when a sponsor happens from the extension, and the extension automatically skips sponsors it knows about using a privacy preserving query system. It also supports skipping other categories, such as intros, outros and reminders to subscribe, and skipping to the point with highlight.
For the rest, it's mostly creator specific. If a creator is abusing sentimental music in many videos, or I don't like the way he/she talks. I just hit "unsubscribe" and move on.
Moriarty:
> So you're not fighting me...so much as you are the human condition
- can ML algortihms do these things? yes, to all of your points
- can you realistically run such an ML service? only if you're youtube.