> Imagine for example that the camera in a certain locale had some debris on it, but it's a unique shape and location on the lens.

I believe Facebook patented a method for using lens imperfections (dust, scratches, etc.) - see https://news.ycombinator.com/item?id=18835377

The patent office is going to change it so if a generic neural network put to a task learns the same technique as a human patent, the patent fails the ordinarily skilled in the art test.

Human geoguessr players use cheats like like less defects or other accidents with the captures.

You’re right, I totally neglected to point that out. I more so meant the AI is far better and doing this than humans are, and it’s wrong to say most/all humans can’t do it. We just can’t do it as well or as thoroughly as the AI can.

Rainbolt also uses these tricks wherever possible. Eg pro geoguesser players know how high the camera angle is on street view in each country, and which countries the edge of the Google car is visible on shot.

Definitely, that’s worth mentioning and I was arguably wrong to say most or all humans couldn’t do it. Many of the things the AI did really are things humans do. I think what I meant to say is that the depth and breadth in which the AI can do it is superhuman. Like, tiny bits of dust on the lens a person couldn’t really see become clearly and reliably identifiable features of locales. We can use aspect, seams, and other more obvious features of camera images in specific areas, but the AI can go quite a lot further using minute and sometimes almost imperceptible details.

This reminds me of the Tank neural net urban legend:

https://gwern.net/tank