Stefano Ermon: Satellite images can pinpoint poverty better than surveys

One of the biggest challenges in poverty mitigation is that we don’t have good poverty data. Stefano Ermon, assistant professor of computer science and a fellow at the Woods Institute for the Environment at Stanford, is developing a machine learning model that uses high-resolution satellite images to inexpensively generate accurate poverty maps for entire countries or continents. Watch his talk at the 2016 Global Entrepreneurship Summit partner event, “The Future of Artificial Intelligence,” to learn more.