Stanford Students’ PIGEON AI Outperforms Humans in Geolocation Challenge

In a groundbreaking project named Predicting Image Geolocations (PIGEON), three Stanford graduate students have demonstrated the remarkable geolocation capabilities of artificial intelligence (AI). The project, initially designed to identify locations on Google Street View, showcased AI’s potential to accurately determine the origin of personal photos it had never encountered before.

Inspired by their shared enthusiasm for the online game GeoGuessr, the trio—Michal Skreta, Silas Alberti, and Lukas Haas—sought to develop an AI player capable of outperforming human participants in geolocating photos. GeoGuessr, with its 50 million players worldwide, became the playground for their ambitious experiment.

The students built upon the existing CLIP neural network, developed by OpenAI, to analyze images by reading accompanying text. Their training dataset comprised approximately 500,000 images from Google Street View.

 

 

 

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