In this talk, Dr. Steven Mirsky explores how the future of autonomous agriculture hinges on developing open-access, annotated images libraries to train computer vision models. While the tools for AI-driven farming—robots, sensors, and computer vision—are advancing rapidly, the real bottleneck is the availability of open, high-quality training data and accessible, modular hardware. Dr. Mirsky makes the case that to truly unlock autonomy in agriculture, we must first digitize the farm and then democratize the data and tools that power intelligent systems. He outlines how an open ecosystem of AI, data, and hardware can enable precision sustainable agriculture. Steven Mirsky leads the Sustainable Agricultural Systems Laboratory at the USDA Agricultural Research Service. For over 25 years, he has advanced sustainable and precision agriculture for field crop producers. Most recently, he launched the Digital Agricultural Systems Hub (DASH), USDA’s enterprise platform for developing computer vision and AI solutions deployed by plant scientists, breeders, and farmers.Through DASH, he is accelerating the path to agricultural autonomy by building and curating AgIR—the National Open-Access Plant Image Repository—and developing PlantMap3D, a modular camera system designed for plant phenotyping and precision farming applications. Dr. Mirsky holds a B.A. in Agroecology, an M.S. in Soil Fertility and Quality, and a Ph.D. in Agronomy with a focus on Weed Ecology. He has published approximately 150 peer-reviewed journal articles. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx