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>It was established that, whilst analytics could not confidently detect a theft, but they could detect a person with a bike

Really groundbreaking stuff. I'm so happy public funds are being used to pump surveillance data to a mega-corporation so they can tell us who does or does not have a bike.

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It seems like there actually was some value to this part:

> allowed police to speed up investigations into bike thefts by being able to pinpoint bikes in the footage

Normal procedure as far as I know is you keep recordings for 48h or whatever, and if someone reports their bike as stolen a human reviews the footage to see if they can find anything. If you can use ML or something to tag the snippets in the last 24h that contain bikes being moved, that's more efficient use of taxpayer-funded police officers' time?

It's also something that somebody with little to no previous knowledge of machine learning could whip up with OpenCV in a weekend. Maybe they could hire an undergrad to do it as a student project instead of giving Amazon unfettered access to their surveillance data?

That's just not true. Maybe you could whip something up that could detect a bike under select circumstances, but a robust system that could actually be used as a tool is a much harder project.

Ah yes, bike, no bike

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