Transforming the Way the World Produces Food:
The AI Advantage

Precision agriculture harnesses AI to elevate the efficiency, productivity, profitability and sustainability of farming.

Solving Precision Farming Challenges with AgTech Robotics

AgTech robotics solves precision farming challenges through the convergence of autonomous vehicle technologies with IoT sensors. AgTech robotics ensures accurate positioning, optimizes crop monitoring and distribution through real-time data insights leading to enhanced harvesting capabilities. AgTech robotics demands the best-in-class AI solutions optimized for the edge, a significant shift from the incumbent solutions that were optimized for graphics displays.

Re-thinking AI Inference Acceleration Solutions for AgTech Applications

Vision AI in AgTech empowers farmers with the capability for precise object detection and classification, thereby streamlining tasks such as crop monitoring and pest identification. This enhances operational efficiency by reducing manual labor and allowing for proactive intervention against potential threats to crops, ultimately leading to improved yield quality and quantity.

Through AI, crops and soil receive the precise amount of fertilizer and herbicides ensuring optimal health for maximum crop production. This targeted approach not only boosts profitability by increasing yields, but also promotes more efficient use of resources, reducing waste and environmental impact.

 

Untether AI’s energy-efficient architecture is based upon at-memory computation delivering the highest compute performance at industry-leading levels of efficient power consumption. To the farmer, this means more crops harvested or fertilized per minute while using less fuel, fertilizer, and herbicides.

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Ask Us About AI for AgTech

Our AI accelerators offer high-performance, low-power, small-footprint solutions for AgTech system architects. Contact us to find out how we can support your efforts in re-thinking your approach to designing AgTech solutions and architectures.

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