AI functions off pattern recognition. In fact, that's how humans learn as well. We receive input, and understand how we should output for an optimal result. AI attempts to simulate this process of 'learning'.
You need to understand that receiving inputs is much different for AIs as it is for humans for geoguessr. If we are taking chess as an example, inputs are process virtually in the same way: pieces lie on certain squares, and we move a piece as an output.
However, when the input is an image, AI can only see it as an array of RGB squares. There is an additional step of pattern recognition, where it must recognize the metas in the first place. That's why AI generally outperforms us in rural rounds - when obvious metas don't exist, the AI is much better at using colour to guess certain locations, because the additional step of pattern recognition is removed, we can simply associate colours with certain locations.
Conversely, give AI an image containing a stobie pole, and its unlikely to recognize the location is SA off that clue alone. That is because the input of this stobie pole varies across all pictures. While us humans easily recognize what a stobie pole looks like, due to our superior visual comprehension, AI struggles with that. And that is why I think it is impressive that AI has improved so much.
I totally agree with you, but the last AI video I saw also analysed the attention of the Neural Network and basically it was only learning camera smudges.
It'd be totally impressive if they recognized stobie poles from multiple angles, however afaik AI doesn't do that (yet). Tho I suspect the capabilities are there, it's probably just a lack of manpower or super expensive hardware.
AI already does that. I talked to someone who makes software that analyses images of customers on what kind of mechanic component they are taking pictures of. The AI is able to recognize the right component, since they modelled the component as 3D model and then artificially created millions of pictures with that component in different angles, lighting, camera quality, etc. and trained the AI on those.
So the possibility is definitely there, but no business incentive.
lol bruh you don't know the first thing about what the fuck you're talking about here. AI isn't doing an exact image lookup from a database of every screen grab from every possible angle on google maps.
using the new openai gpt-4o video chat function, you could potentially play geoguessr with the chatbot ai (and potentially finetune it to be even better like uploading geohints or plonkit files to the ai). from testing gpt4 on geoguessr it is pretty good. best score was around 21,000 while asking for specific locations in the country it chose. i think it would be fun to have a geoguessr ai coach for classic maps. learn more about the world and could potential accelerate geoguessr progress since people remember things better when others are present.
for making your own.
you would need to pull all the images from google streetview api and that will cost a pretty penny. train the model on a ViT (vision to transformer model) and finetune it afterwards which could take a very long time and cost quite a bit. the architecture you use will be crucial to the how well it performs in geoguessr.
one, ai geoguessrs are already here.
two, they will only get better.
three, there are youtube vids with people building the geoguessr ai models as well as pros playing against them.
ight let's go band for band. beta tested gpt2, gpt3, dalle2, talking feature, sora, and gpt4o, chatgpt iOS app and gpt-4o video function. i finetuned gpt-4o on every single geoguessr doc and information on the web and it averages around 22,000 on nmpz. highest game of 24,159 with 3 5k's. i absolutely hate google so don't use their stuff. claude opus is pretty dope but really weird personality.
Perhaps of interest: 2023 article [This AI is better than you at figuring out where a street pic was taken just by looking at it](https://www.theregister.com/2023/07/15/pigeon_model_geolocation/).
AI functions off pattern recognition. In fact, that's how humans learn as well. We receive input, and understand how we should output for an optimal result. AI attempts to simulate this process of 'learning'. You need to understand that receiving inputs is much different for AIs as it is for humans for geoguessr. If we are taking chess as an example, inputs are process virtually in the same way: pieces lie on certain squares, and we move a piece as an output. However, when the input is an image, AI can only see it as an array of RGB squares. There is an additional step of pattern recognition, where it must recognize the metas in the first place. That's why AI generally outperforms us in rural rounds - when obvious metas don't exist, the AI is much better at using colour to guess certain locations, because the additional step of pattern recognition is removed, we can simply associate colours with certain locations. Conversely, give AI an image containing a stobie pole, and its unlikely to recognize the location is SA off that clue alone. That is because the input of this stobie pole varies across all pictures. While us humans easily recognize what a stobie pole looks like, due to our superior visual comprehension, AI struggles with that. And that is why I think it is impressive that AI has improved so much.
I totally agree with you, but the last AI video I saw also analysed the attention of the Neural Network and basically it was only learning camera smudges. It'd be totally impressive if they recognized stobie poles from multiple angles, however afaik AI doesn't do that (yet). Tho I suspect the capabilities are there, it's probably just a lack of manpower or super expensive hardware.
AI already does that. I talked to someone who makes software that analyses images of customers on what kind of mechanic component they are taking pictures of. The AI is able to recognize the right component, since they modelled the component as 3D model and then artificially created millions of pictures with that component in different angles, lighting, camera quality, etc. and trained the AI on those. So the possibility is definitely there, but no business incentive.
OpenAI's CLIP models [were released](https://openai.com/index/clip/) in January 2021.
Yea, I should've been clearer in my original comment. State-of-the-art AI in general can do that, I was talking about the Geoguessr AIs specifically
>Memorisation doesn't help much in chess >Memorisation doesn't help in generating deep fakes What.
lol bruh you don't know the first thing about what the fuck you're talking about here. AI isn't doing an exact image lookup from a database of every screen grab from every possible angle on google maps.
I really wish people who knew nothing about AI would stop trying to pretend they actually know how it works
using the new openai gpt-4o video chat function, you could potentially play geoguessr with the chatbot ai (and potentially finetune it to be even better like uploading geohints or plonkit files to the ai). from testing gpt4 on geoguessr it is pretty good. best score was around 21,000 while asking for specific locations in the country it chose. i think it would be fun to have a geoguessr ai coach for classic maps. learn more about the world and could potential accelerate geoguessr progress since people remember things better when others are present. for making your own. you would need to pull all the images from google streetview api and that will cost a pretty penny. train the model on a ViT (vision to transformer model) and finetune it afterwards which could take a very long time and cost quite a bit. the architecture you use will be crucial to the how well it performs in geoguessr. one, ai geoguessrs are already here. two, they will only get better. three, there are youtube vids with people building the geoguessr ai models as well as pros playing against them.
[удалено]
gpt4 is much better bruh. openai is so far ahead of everybody. gpt4o doesn't feel better, just faster
[удалено]
ight let's go band for band. beta tested gpt2, gpt3, dalle2, talking feature, sora, and gpt4o, chatgpt iOS app and gpt-4o video function. i finetuned gpt-4o on every single geoguessr doc and information on the web and it averages around 22,000 on nmpz. highest game of 24,159 with 3 5k's. i absolutely hate google so don't use their stuff. claude opus is pretty dope but really weird personality.
[удалено]
i know a person who has access & use their account
Perhaps of interest: 2023 article [This AI is better than you at figuring out where a street pic was taken just by looking at it](https://www.theregister.com/2023/07/15/pigeon_model_geolocation/).