Imagine one hundred years ago if farmers had access to huge volumes of information about the soil profile of their land, the varieties of crops they were growing, and even the fluctuations of their local climate. This kind of information could have prevented an environmental crisis like the Dust Bowl of the 1920s in the American Midwest. But even ten years ago, the idea that farmers could have access to this kind of information was unrealistic.

For the team behind the CGIAR Platform for Big Data in Agriculture, farming is the next frontier for using artificial intelligence (AI) to efficiently solve complex problems. The team—which includes biologists, agronomists, nutritionists, and policy analysts working with data scientists—is using Big Data tools to create AI systems that can predict the potential outcomes of future scenarios for farmers. By leveraging massive amounts of data and using innovative computational analysis, the CGIAR Platform is working to help farmers increase their efficiency and reduce the risks that are inherent in farming.

The idea behind the CGIAR Platform is to first create a better way for researchers to manage and share agricultural data. This is a huge project by itself, but the Platform is aiming to be more than just a library of research data. The ultimate goal is to seamlessly integrate real-world data from farms around the world into algorithms that generate critical insights that can then be shared back with farmers.

Read the full article on artificial intelligence in agriculture by Elliott Brennan at Food Tank.