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Mapping the modern world: How S2Vec learns the language of our cities

Google Research · published 24 March 2026

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https://ai.google/earth-ai/
ai.google
https://dl.acm.org/doi/10.1145/3787217
dl.acm.org
https://en.wikipedia.org/wiki/Rasterisation
en.wikipedia.org
https://s2geometry.io/
s2geometry.io
https://openaccess.thecvf.com/content/CVPR2022/html/He_Masked_Autoencoders_Are_Scalable_Vision_Learners_CVPR_2022_paper
openaccess.thecvf.com
https://ojs.aaai.org/index.php/AAAI/article/view/32457
ojs.aaai.org
https://proceedings.neurips.cc/paper_files/paper/2023/hash/1b57aaddf85ab01a2445a79c9edc1f4b-Abstract-Conference.html
proceedings.neurips.cc
https://arxiv.org/abs/2503.08722
arxiv.org
https://dl.acm.org/doi/abs/10.1145/3486635.3491076
dl.acm.org
https://dl.acm.org/doi/abs/10.1145/3615886.3627750
dl.acm.org
https://en.wikipedia.org/wiki/Mean_squared_error
en.wikipedia.org
https://research.google/blog/insights-into-population-dynamics-a-foundation-model-for-geospatial-inference/
research.google
Google Earth AI: Unlocking geospatial insights with foundation models and cross-modal reasoning Read at the source ↗
research.google