By 2030, John Deere aims for fully autonomous farming, addressing global challenges like labor shortages, sustainability, and food security. Their AI and robotics solutions make farming more efficient and profitable, reduce environmental impact, lower carbon footprints, and promote biodiversity.
In this session, Chris Padwick, director of Machine Learning and Computer Vision at John Deere, outlines how AI and robotics advance agriculture through their autonomous tractor and See & Spray system. Leveraging deep learning and computer vision to optimize resource use and increase productivity, these technologies help farmers by automating tasks like precision herbicide application, reducing chemical usage, conserving resources, and improving crop yields.
Follow along with a PDF of the session as Padwick discusses how the collaboration with NVIDIA, dating to participation in the NVIDIA Inception Program, has been instrumental in accelerating the development of these AI-driven systems. Powered by NVIDIA GPUs, John Deere’s connected machines gather and process real-time data on-site, enabling autonomous systems to make real-time decisions every 20–80 seconds, even in challenging conditions.
This is a must-watch for anyone interested in the future of agriculture and how cutting-edge AI and robotics are reshaping the industry. You’ll learn how AI-powered autonomous systems can tackle global challenges while gaining insights into how computer vision, edge computing, and real-time data processing drive sustainable farming.
Watch the advanced talk on Transforming Agriculture with AI and Computer Vision, explore more videos on NVIDIA On-Demand, and gain valuable skills and insights from industry experts by joining the NVIDIA Developer Program.
This content was partially crafted with the assistance of generative AI and LLMs. It underwent careful review and was edited by the NVIDIA Technical Blog team to ensure precision, accuracy, and quality.