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NVIDIA® Jetson™ Powered Edge AI Devices Guide

NVIDIA® Jetson™ brings accelerated AI performance to the Edge in a power-efficient and compact form factor. The Jetson family of modules all use the same NVIDIA CUDA-X™ software, and support cloud-native to build, deploy, and manage AI at the edge across all industries. Seeed is the authorized reseller of NVIDIA Jetson Developer Kits and Elite Partner of the NVIDIA Jetson ecosystem. Based on our with our over 15 years of hardware expertise, we offer a one-stop experience to simplify edge AI development including standard carrier boards and devices family, ODM services of both hardware & image flashing. Together with leading AI ecosystem partners, Seeed speeds time to market for customers by handling integration, manufacturing, fulfillment, and distribution.

Click here to learn more about the comparison between the NVIDIA Jetson powered devices
Jetpack Flash and Hardware Usage
Most of our reComputer Jetson products come with NVIDIA JetPack system pre-installed on the device. However, if you want to flash these devices again or flash other devices which do not come with JetPack system, you can follow the below links for step-by-step guidance. We have also included guidance on how to use different hardware peripherals on these NVIDIA Jetson powered devices.
Note: Hover your mouse over the product name on the left hand side and click it to enter the relevant wiki pages. Also hover your mouse over the product series name on the right hand side to have a glimpse of the products included in that series.
AI Developer Tools
After you have access to an NVIDIA Jetson device, you can start developing different AI applications to suite different scenarios. The very first step of an AI project is to obtain data for training. Then you need to label the data and train an AI model. After that, you can optimize this model to make sure the model runs the best on the selected device. Finally, you deploy this AI model to the NVIDIA Jetson device so that you can start building applications. You can also manage these applications remotely so that, you can track the device performance metrics to ensure the device is performing well in the field. We have prepared wiki guides that covers the entire AI workflow as explained above using different software providers and tools.
Note: Hover your mouse over the software tool on the left hand side and click it to enter the relevant wiki pages. Also, hover your mouse over the task on the right hand columns to have a glimpse of the software providers and tools relevant for that task.
Updates to this page are in in progress. Stay tuned!
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