I can see the surveillance network providing vastly more training data. But isn't that orthogonal with developing the algorithms?

Or is it that training data provides experience, which improves the algorithms? Or the application of the algorithms?

It’s a positive loop. More effective surveillance network -> Larger investment (from government or government contract) -> more application/startup/new programs -> more research funding/aggressive hiring -> higher recognition for CV/ML researchers/Engineers -> More and more people doing CV/ML -> More data, algorithms and applications-> more effective surveillance network. Btw it got deployed at scale in real world which is a huge advantage for progressing any CVML research

Not to mention nowadays Deep learning is pretty much a big data game.

> But isn't that orthogonal with developing the algorithms?

Assuming it is - China is also competitive on developing algorithms. A few months ago there was a post on explosion of AI papers submitted by authors at Chinese research institutions, with no signs of slowing down.

It's not just availability of data for training networks; I was mainly referring to practical engineering know-how built by field experience