Post #3324502
2026-06-08 04:03 UTC
Using a LLM for detecting a specific object on an image is possible but stupid: if your object is always the same (like in this case) it’s several orders of magnitude cheaper to train once on that specific object then use the computer vision model running directly on the local server that’s recording the video.
Otherwise:
the api costs would be colossal, 0.001$ per each image, at 30 fps it’s $100 per hour, nobody would pay that
The detection latency would be several seconds vs almost instant
Without internet connection the system wouldn’t work
Use cases for LLM-based image recognition is if the object changes at every request or it’s ultra specific with brands and colors
Replies (1)
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@db2@lemmy.world 2026-06-08 04:23
if your object is always the same (like in this case) It isn’t the same though. A large gauge shotgun and a small gauge pistol are pretty different looking. Compare those to a .22 rifle with a scope, and those to a decked out ar15. That’s a lot of different always the sames. What if it’s a revolver? Or has a folded stock? Or a sawed off stock? Will it recognize a derringer or a mac10 with a large capacity mag as guns? We can because they make us dead. We have valid reason to fear them which is a great motivator for most species to learn to recognize the danger. You’d still recognize a ring gun as a gun, without getting specifically trained to do so a machine will identify it as jewelry.