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

What this post added

This post details the open-sourcing of training data and sample code for Meta's AI-powered population maps. It explains the methodology, which uses computer vision to identify buildings in satellite imagery and combines this with population stock estimates. The post highlights the applications of these maps in disaster preparedness, climate adaptation, and sustainable energy, and provides examples of their use by organizations like the World Bank and World Vision. It also discusses the importance of accurate population data in low- and middle-income countries and the ongoing collaboration with external partners.