this post was submitted on 23 Aug 2026
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Let's do some order of magnitude math... Let's say each car on average "sees" 100 things a day (which is very conservative since there's multiple cameras and with basic object recognition you're going to have a lot of false duplicates). Let's say each picture is cropped to a megabyte with compression, which would be pretty low res to grab identifying information from
You can't do much in the way of video compression, because this isn't a video - we're cropping pictures, too much will change frame to frame
So 100MB a day per car, that's nothing... For one car. How many cars are doing this? 10 million? 50 million?
(Oh, and btw 5G is basically just 4G or 3G outside of Metro areas in the US)
It detects faces well, that's easy enough, and it can generally label the people because you only have so many in the pool of subjects. If you want to identify people in a population? You're not doing that on a phone. Even the best systems have a big problem with false matches
Parking lots are not usually good vantage points... That's where most cars live
And as for disparate data points... Unless ever auto company is using the same system, it's going to take non negligible amounts of work to integrate different systems. Palantir is probably going after the lower hanging and more juicy fruit, like Ring doorbells and commercial security systems. Or, you know, phones
That's what it comes down to. All this for what? I'm not saying they wouldn't do it, or it couldn't be done, I'm saying there's better options that they are already using for surveillance
If they were to do it, you'd pick Tesla - they have the cameras and sell monitoring as a feature. They're reasonably widespread, so you'll get almost the same coverage as if all automakers were on board - remember, this is about tracking people and vehicles, if we're recording them we're in a whole different ballpark
Or, you know, set up 100k cameras at key intersections and get a more comprehensive system with a lot less moving pieces