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> reliable sources Which? Seems like activists may want us to believe that they have lots of RAM so they'll get stolen, and Flock may want us to believe that

by fwipsy 2mo ago

> reliable sources Which? Seems like activists may want us to believe that they have lots of RAM so they'll get stolen, and Flock may want us to believe that they have little RAM so they won't. Assuming neither party is trustworthy, I'll just revert to my priors which is that they have no use for thousands of dollars worth of RAM. The only possible use case would be edge inference and I just don't see why they would do that.

tgsovlerkhgsel 2mo ago
> The only possible use case would be edge inference and I just don't see why they would do that. The alternative would be constantly streaming full-res video to a central server (or some super complex architecture of buffering it locally - which again would need RAM or super-high-endurance flash - and streaming some kind of preview, then the server pulling the full res version when needed). Any blip in network connectivity would cause data loss. Uncompressed 4k video at 30 fps is 3840x2160x30x3 bytes or 0.75 GB per second.
- malfist 2mo ago
  A) why would they be storing uncompressed video, that's ridiculous. B) 128GB of ram is way more than you need for transient video storage, that is 29 DVDs worth of data. C) You are not constrained to only store data in RAM
voakbasda 2mo ago
There is virtually no question they are doing inference at the edge. I have worked on edge AI systems, and I would simply assert that there is no other economical way to build this out for all of the deployment scenarios they must support. Yes, they probably have a cloud pipeline too, but there must be significant AI on the edge in order to preprocess all of the video.
- fwipsy 2mo ago
  You're right. I didn't think that through. Actually, that's probably the stupidest thing I said all day. (I hope so, anyways.) However, I'm skeptical that 32GB RAM is necessary for what they do on the edge. Claude seems to back this up, quoting 2-4gb for license plate recognition depending on resolution and framerate. but I'm open to correction here.

by fwipsy 2mo ago

tgsovlerkhgsel 2mo ago

> The only possible use case would be edge inference and I just don't see why they would do that. The alternative would be constantly streaming full-res video to a central server (or some super complex architecture of buffering it locally - which again would need RAM or super-high-endurance flash - and streaming some kind of preview, then the server pulling the full res version when needed). Any blip in network connectivity would cause data loss. Uncompressed 4k video at 30 fps is 3840x2160x30x3 bytes or 0.75 GB per second.

malfist 2mo ago
A) why would they be storing uncompressed video, that's ridiculous. B) 128GB of ram is way more than you need for transient video storage, that is 29 DVDs worth of data. C) You are not constrained to only store data in RAM

voakbasda 2mo ago

There is virtually no question they are doing inference at the edge. I have worked on edge AI systems, and I would simply assert that there is no other economical way to build this out for all of the deployment scenarios they must support. Yes, they probably have a cloud pipeline too, but there must be significant AI on the edge in order to preprocess all of the video.

fwipsy 2mo ago
You're right. I didn't think that through. Actually, that's probably the stupidest thing I said all day. (I hope so, anyways.) However, I'm skeptical that 32GB RAM is necessary for what they do on the edge. Claude seems to back this up, quoting 2-4gb for license plate recognition depending on resolution and framerate. but I'm open to correction here.