Researchers propose ways to apply AI to agriculture and conservation

During a workshop hosted at the International Conference on Learning Representations (ICLR) 2020, taking place on the web this week, panelists discussed how AI and machine learning might be -- and already has been -- applied to agricultural challenges. As several experts pointed out, countries around the world face a food supply shortfall -- an estimated 9% of the population (697 million people) are severely "food insecure," meaning they're without reliable access to affordable, nutritious food. Factors like labor shortages, the spread of pests and pathogens, and climate change threaten to escalate the crisis. IBM scientists spoke about their work in Africa with agricultural "digital twins," or digital models of crops used to forecast specific crop yields. And a team from the University of California, Davis detailed an effort to use satellite images to predict foraging conditions for livestock in Kenya.