Comment on Are those top tier Geoguessers that do crazy stuff like figure out a location from 4 pixels and a mcslurry contracted by the CIA?

SGforce@lemmy.ca ⁨1⁩ ⁨month⁩ ago

• someguy3@lemmy.world ⁨1⁩ ⁨month⁩ ago

  There really are some good geoguessers. It’s not a crowd source game.

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• SolOrion@sh.itjust.works ⁨1⁩ ⁨month⁩ ago

  It’s 100% not about crowdsourcing. Idk how that even makes sense- do you know what Geoguessr is?

  There’s some people that are absolutely cracked at geoguessr. Rainbolt, for example.

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• alcoholicorn@lemmy.ml ⁨1⁩ ⁨month⁩ ago

  A thousand people can take guesses, but only a skilled player can say “Oh yeah, that foliage looks like San Juan or some other mountainous region of Argentina”, or “That black electrical tape is a Nigeria thing”

  People who live in those places aren’t likely to notice how their electrical poles are different.

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• 0x0@lemmy.dbzer0.com ⁨1⁩ ⁨month⁩ ago

  Not to pile on here, but this is not an instance of the birthday problem.

  The birthday problem would kick in if we asked “what are the chances that any two of these N people know the same place, whatever it may be.”

  But instead we’re discussing “what are the chances that one of these N people recognizes a specific place P.”

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  • Deestan@lemmy.world ⁨1⁩ ⁨month⁩ ago

    there are many details in one image, and the chances of some player recognizing one of those details is an instance of the birthday problem?

    That would be a valid model. But you are still right that it doesn’t apply: It would give the effect that a different geoguesser would get the picture right every test, while we are seeing consistent results from the top geoguessers.

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• Deestan@lemmy.world ⁨1⁩ ⁨month⁩ ago

  I see your point, but the Birthday Problem would apply differently.

  It is the chance of “collision” between randomly picked elements two large enough sets of random data. If I understand correctly, the random data here would be “geographical fact” like bush density and road width. Set A is geoguessers’ geographical knowledge, and set B is pictures’ geographical features.

  So if we picked hundreds of random picture and hundreds of geoguessers and asked them, the chance of one guessing one image is high. And the person would be largely dfferent every time.

  In this case, we can give one specific geoguesser a large amount of pictures and that same geoguesser would get most of them right.

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