HAI Weekly Seminar with Stefano Ermon
AI for Sustainable Development
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AI for Sustainable Development
The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.

The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.

AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.

While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
Recent technological developments are creating new data streams that contain a wealth of information relevant to sustainable development goals. Modern AI techniques have the potential to yield accurate, inexpensive, and highly scalable models to inform research and policy. A key challenge, however, is the lack of large quantities of labeled data that often characterize successful machine learning applications. In this talk, Stefano will present new approaches for learning useful spatio-temporal models in contexts where labeled training data is scarce or not available at all. He will show applications to predict and map poverty in developing countries, monitor agricultural productivity and food security outcomes, and map infrastructure access in Africa. His methods can reliably predict economic well-being using only high-resolution satellite imagery. Because images are passively collected in every corner of the world, his methods can provide timely and accurate measurements in a very scalable end economic way, and could revolutionize efforts towards global poverty eradication.
