How open source AI can improve population estimates, sustainable energy, and the delivery of climate change interventions

This post details the open-sourcing of training data and sample code for Meta's AI-powered population maps. The dataset includes nearly 10 million labels for over 126 gigabytes of satellite imagery, indicating the presence of buildings. This data, collected between 2011-2020, aims to train machine vision models to more accurately identify buildings in various environments. The release is intended to assist researchers in improving population estimates for applications in climate adaptation, public health, disaster response, sustainable energy, and climate-resilient infrastructure.