Unleashing AI Power at the Edge: Ubuntu Meets NVIDIA Jetson

In the rapidly evolving world of artificial intelligence, the ability to process data at the edge is becoming increasingly crucial. Canonical has officially announced Ubuntu support for NVIDIA Jetson modules, creating new opportunities for AI-driven innovation in industries such as autonomous machines, smart cities, industrial automation, and robotics.

With over 500 hardware compatibility tests, optimized Ubuntu images, and enterprise-grade security, this collaboration empowers developers and enterprises to push the boundaries of AI at the edge. This blog explores the benefits of Ubuntu on NVIDIA Jetson, the supported devices, the installation process, key developer features, and Canonical's extended offerings.

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Canonical and NVIDIA's Collaboration for AI at the Edge

Partnership Goals and Target Industries

Canonical and NVIDIA have partnered to enhance AI capabilities at the edge, focusing on key industries:

• Autonomous Machines: AI-powered robotics and self-driving systems.

• Smart Cities: AI-enhanced infrastructure, security, and monitoring.

• Industrial Automation: AI-driven process automation and efficiency.

This collaboration aims to:

• Maximize AI performance on NVIDIA Jetson platforms.

• Provide enterprise-grade security and long-term support.

• Streamline AI development from concept to production.

Key Benefits:

• Optimized Ubuntu images: Improved AI performance on Jetson.

• Extensive compatibility testing: Ensures system stability.

• Seamless development-to-deployment: Enhances productivity for AI developers.

Partnership Aspect	Benefit
Optimized Ubuntu images	Improved performance on NVIDIA Jetson
Extensive compatibility testing	Guaranteed system stability
Seamless development-to-deployment	Enhanced productivity for developers

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Supported NVIDIA Jetson Devices

Ubuntu's official support extends to the entire NVIDIA Jetson Orin™ lineup, ensuring optimal performance for edge AI and robotics applications. Supported devices include:

• Jetson AGX Orin

• Jetson Orin NX

• Jetson Orin Nano

These devices offer a scalable platform for AI workloads, from low-power applications to high-performance deep learning tasks.

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Ubuntu Installation and Customization

Installing Ubuntu on NVIDIA Jetson devices is a straightforward process. Users can download an optimized Ubuntu image, flash it onto their Jetson hardware, and begin development. Key steps include:

1. Selecting the appropriate Ubuntu OS image for the Jetson model.

2. Flashing the OS onto a USB, NVMe, or microSD card.

3. Booting and configuring Ubuntu with necessary dependencies and AI frameworks.

4. Customizing the system with additional software, including TensorFlow, PyTorch, and ROS.

With support for Ubuntu Core, developers can also create custom production images for specific AI applications.

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Advancing Robotics and AI Development

With Ubuntu’s official support, Jetson-powered robotics and AI applications can now benefit from:

• Optimized AI inference using TensorRT and CUDA acceleration.

• Seamless integration with ROS (Robot Operating System).

• Edge AI model deployment with enhanced performance and low latency.

This enables industries such as healthcare, logistics, and manufacturing to build more efficient, AI-driven automation solutions.

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Key Features for Developers

For AI and robotics developers, Ubuntu on Jetson provides:

• Enterprise-grade security with regular updates and patches.

• AI-ready environment with pre-installed frameworks like TensorFlow, PyTorch, and ONNX.

• Efficient device management with over-the-air updates for production systems.

• Agile containerization using Docker and Kubernetes.

• Hardware-accelerated AI leveraging NVIDIA’s GPU and deep learning frameworks.

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Canonical's Extended Offerings

Canonical provides additional solutions for AI and edge computing, including:

• Ubuntu Core: A minimal, secure OS for IoT and edge devices.

• Long-term support (LTS): Ensuring stability and security for AI deployments.

• Silicon Partner Program: Collaboration with hardware vendors for optimized Ubuntu images.

• Cloud-to-Edge AI Deployment: Enabling seamless AI development across cloud and edge environments.