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Advances in artificial intelligence (AI) are revolutionizing weather forecasting for agriculture. Experts announced that AI models can now deliver faster, cheaper, and hyper-local predictions. This breakthrough extends access to regions that previously lacked advanced forecasting technologies.

Supported by the Agricultural Innovation Mechanism for Scale (AIM for Scale), researchers from Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and the University of Chicago revealed plans to help governments in low- and middle-income countries adopt these innovations. The program aims to build world-class national services, previously available only in highly developed regions.

Pedram Hassanzadeh, associate professor at the University of Chicago, reported, “AI weather models are transforming forecasting, but governments often lack training and infrastructure. We are ensuring these countries harness AI to benefit farmers.”

The UAE-funded initiative trains staff from national meteorological and agricultural services. The first cohort includes participants from Bangladesh, Chile, Ethiopia, Kenya, and Nigeria. Training takes place at MBZUAI and the National Center of Meteorology in the UAE. Future rounds will expand to 25 more countries, potentially reaching millions of farmers.

  • Accurate forecasts can boost yields, incomes, and livelihoods.
  • The program provides high-performance multi-GPU laptops for practical application.
  • Ministries help tailor forecasts to local farmers’ needs.

Paul Winters, Executive Director of AIM for Scale, revealed that pairing AI innovation with agricultural decision-making opens new opportunities for farmers worldwide. The training covers weather data, model verification, and downscaling to help farmers plan under uncertainty.

The initiative partners with global institutions including Google DeepMind, ECMWF, AfriClimate AI, and the World Meteorological Organization. Amir Jina, assistant professor at UChicago, reported, “This program demonstrates how AI can be operationalized for the global good, giving low- and middle-income countries access to gold-standard forecasts.”