Regardless of the computational needs to facilitate mass surveilance, there are inescapable storage needs precipitated by surveilance. Governments want to retain data because its value in the future is unknown in the present. This is the entire premise behind the Harvest Now Decrypt Later[0] principle that fuels much of the previous surveilance actions taken by governments. But HNDL is speculative; it either hedges on the bet that computational breakthroughs will weaken encryption methods to the point where brute force attempts at decryption are not financially feasible for most actors but still physically possible, or rely on a backdoor in an encryption algorithm to decrypt data that is valuable. There has been much speculation about this feasibility and value RE: quantum computation and also the design of encryption algorithms from the ground up (see things like the Clipper Chip and RSA's relationship with the NSA).

With things like video, photo, audio, and liturgical surveilance, the data is largely out in the open (or simply purchased from their hosting platforms, leading to social media and adtech companies like Facebook and Google being defense contractors by nature) and does not need to be decrypted (in most cases) - rather, it needs to be correlated. This is a great task for machine learning because that's what the field has largely been engineered to do for the last 60 years, but it relies so, so, so heavily on having data to both train on and use in its practice. Storage of all data is the perfect end-goal of a surveilance state. Storage requires data centers. Data centers of this calibre are effectively black sites in that they are nigh impenetrable in both practical and legal senses, and I'd wager many data centers host actual digital black sites simply due to their ubiquity as means of doing so coupled with the necessity of the hardware and facilities they provide that are needed for doing so.

Theres really nothing that will ever be publicly available that would say "this data center has a hundred thousand SOTA GPUs in it that are doing gait recognition on every camera in every airport in the world in real time" versus "this data center is a bunch of tape machines that store everything ever recorded from every facsimilie of Room 641A[1]".

0: https://en.wikipedia.org/wiki/Harvest_now%2C_decrypt_later

1: https://en.wikipedia.org/wiki/Room_641A

Video-processing AI can be very flexible in its demands.

Even if a camera supports 4k 60fps video, the 'edge AI' can downscale the input to 224x224 2fps and use a small network.

Often the 'edge AI' just needs to detect humans/cars/pets and trigger saving some footage to an SD card/turning on a light. It's not the end of the world if it misses some things or raises false alarms sometimes.

And if you buy a Reolink on Amazon expecting it to be able to recognise a face from 20 yards away, you'll be disappointed.

IMO you highly underestimate the amount of processing and storage video surveillance requires. There is just no good way to determine if you took that pen or made the newly illegal handgesture towards the wrong person 12 years ago unless you have enough storage to keep all the footage around and the processing power to search through it or prepare it for new types of queries in reasonable time.

Also, have you considered AI being necessary to fill in for missing surveillance footage if the cameras are failing (the ruling class)? E.g. the whole Epstein (PR) disaster could have been avoided if the cameras could have been kept running and the footage post-processed in time.