The agri-food sector has yet to embrace fully the transformative power of artificial intelligence. AI holds the potential to assist farmers by identifying problems and offering solutions based on verifiable real-time information. For instance, predictive crop and pest models could help agricultural producers prevent outbreaks and reduce pesticide use. The challenge is that researchers developing advanced data analysis platforms often do not understand the agri-food sector well enough to conceive of relevant applications for their breakthroughs. Similarly, agri-food sector professionals tend not to know enough about the high-tech world to take advantage of the benefits available through the adoption of emerging technologies.
Another impediment to developing effective algorithms is the lack of accessible, consistent, quality data.
CAAIN will seek solutions to both these challenges. First, by developing a network bridging the agri-food and technology solitudes, connecting those in need with those possessing the technical skills and know-how to help. Second, by investing in projects focused on creating shareable data sets, and by supporting the advancement of the frameworks and digital architecture that will enable the development of new artificial intelligence and machine-learning tools.Our Projects