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Comment by mooneater | Hacker News Reader

someone is about to make a lot of money.

PornHub Network's video segmentation system might already be automated in this way.

I actually was thinking about that too, but automated analysis of video at that scale seems prohibitively expensive unless you are Google or Netflix or something. Serving tons of video through a CDN is one thing, but the compute requirements needed to analyze it all are another.

Not that I have thought too terribly deeply about this, but I have a suspicion that this feature is actually powered by additional metadata sent along with the video by the content provider. It seems logical that if you were to control a vast archive of rapidly growing, extremely similar looking content, you would want to tag just about everything you could about it so you could build product.

I predict there will shortly be some dark future for all of us where we'll be able to don our Facebook nightmare helmets, say a single word, and have a super focused stream of filth blasted directly into our brains like that one scene from Demolition Man. That's where this is all going, right? Gotta be.

This program can classify 1 hour of video in 36 seconds on my low end GTX 960 4GB.

and for PornHub's back catalog, this still take longer than the heat death of the universe

not really. 1 hour of video in 36 seconds it 1,000 hours of video / hour of computation. Assuming you go with a cluster of higher end graphics cards, you could pretty easily perform 100x better. That's 100,000 hours of video processed / hour of computation. I don't know the size of the pornhub back catalog, and I'm scared to search since I'm at work right now, but even if it's hundreds of millions of hours you could go through the whole thing in like 2 months tops.

Isn't 1 hour video in 36 seconds a 100x speedup instead of 1000? Agreed that it's definitely doable if they want.

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