AI-powered technologies empower farmers to make data-driven decisions by analyzing real-time environmental and crop data.
Despite mechanization and advanced equipment, much of modern farming still relies on manual labor, tradition, and intuition. Overuse of herbicides and fertilizers can lead to soil burnout and the industry is seriously challenged with a real labor shortage, which is projected to get worse. These current dynamics call for smarter, more sustainable solutions — precisely where artificial intelligence steps in.
by Ranjani Ramasubramanian
SPECIALTY CHIPS: A robotic laser weeder employs about 24 GPUs and takes about 2.6 weeks to weed 450 acres of farmland. With AI inference chips, it uses 90% less power and finishes the job in just four days. Kinwun/Getty Images
AI-powered technologies empower farmers to make data-driven decisions by analyzing real-time environmental and crop data. These technologies allow farmers to conserve resources while maximizing productivity. For example, AI can predict optimal planting times, regulate irrigation based on moisture levels, and monitor crop health to improve yields. By using vision systems, AI can reduce reliance on harmful chemicals that identify and eliminate weeds and pests.
Farming smarter
Precision agriculture represents the pinnacle of AI’s potential in farming. By integrating AI with internet of things, sensors and satellite imagery, precision farming enables granular resource management. For instance, AI can guide automated irrigation systems to deliver water only where needed, preventing overuse. Similarly, robotic weeders and pest controllers equipped with AI reduce the need for widespread chemical application, preserving soil health and reducing costs.
Today’s ag tech systems often rely on decades-old graphic processing unit technology originally designed for gaming, rather than meeting the specific demands of agriculture. While GPUs offer computational power, they are inherently power-hungry and inefficient for field operations where real-time processing is critical.
For applications like robotic weeders, relying on multiple GPUs significantly increases energy consumption and operational costs, rendering these solutions impractical and unsustainable for large-scale farming operations.
Transforming ag tech
Old GPU solutions that are currently implemented in ag tech have run their course. Purpose-built chips that are catered to the specific demands of agriculture could change the industry.
For example, a robotic laser weeder employs about 24 GPUs and takes about 2.6 weeks to weed 450 acres of farmland. With AI inference chips, it uses 90% less power and finishes the job in just four days.
AI in agriculture is more than a trend. It’s a revolution. As AI technologies continue to advance, the industry will embrace smarter, more sustainable practices, ensuring that farmers can feed the world while preserving its resources for generations to come.
https://www.farmprogress.com/technology/an-ai-revolution-is-happening-in-ag-tech
