I completely agree that this is an incredible advancement as someone who has watched the rise of LLMs' GeoGuessr abilities. I just wanted to qualify the claim m

I completely agree that this is an incredible advancement as someone who has watched the rise of LLMs' GeoGuessr abilities. I just wanted to qualify the claim made in the blog post "In Which I Try to Maintain Human Supremacy for a Bit Longer". I also think that models would need to become far more proficient at tool use (querying OpenStreetMap features, coverage-checking Google Maps, calculating sun direction, etc.) that current human geolocators have access to, and precise spatial reasoning. Additionally, there is a whole corpus of GeoGuessr-specific knowledge that probably wouldn't have a reason to be in model training data (Google Street View coverage quirks, the specific geographic ranges of vegetation and architecture, tiny visual idiosyncrasies in country infrastructure like the width of red on a sign, etc.). However, I think this could probably be solved with more data, and I don't think there is any fundamental barrier.