The BOXER-8110AI by AAEON comes with the NVIDIA Jetson TX2, and it supports 256 CUDA cores and a range of AI frameworks including Tensorflow, Caffe2, and Mxnet. Also, users can install the device with their own AI inference software. These features make the BOXER-8110AI perfect for edge AI applications.

The BOXER-8110AI’s CAN Bus and rugged design features (anti-dust measures, aluminum chassis, wide operating temperature range) mean it is quite suitable for industrial automation and in-vehicle applications. Due to its powerful processor and cost-effective design, the AI platform is ideal for installations anywhere.

The Jetson TX2 is the fastest, most power-efficient embedded AI computing device in the marketplace. This 7.5-watt supercomputer on a module brings real AI computing at the edge. It is built around an NVIDIA Pascal™-family GPU and packed with 8GB of memory and 59.7GB/s of memory bandwidth. It features a variety of standard hardware interfaces, making it easy to integrate it into a wide range of products and form factors.

Features

• NVIDIA Jetson TX2
• Support AAEON ACLinux 4.9, Compliance with Ubuntu 18.04
• 8GB LPDDR4, 32GB eMMC 5.1
• HMP Dual Denver 2 + Quad ARM A57
• HDMI 2.0 x 1, USB3.0 x 2
• RS-232 x 1
• CAN BUS x 2 Channel
• OTG x 1
• LAN x 1
• MicroSD x 1

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Waveshare Jetson Nano Developer Kit - Small Powerful Computer for AI Development Support Running Multiple Neural Networks in Parallel

• NVIDIA Jetson Nano Developer Kit is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.
• Jetson Nano delivers 472 GFLOPS for running modern AI algorithms fast, with a quad-core 64-bit ARM CPU, a 128-core integrated NVIDIA GPU, as well as 4GB LPDDR4 memory.
• It runs multiple neural networks in parallel and processes several high-resolution sensors simultaneously.
• Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), CUDA, cuDNN, and TensorRT software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more.
• The SDK also includes the ability to natively install popular open source Machine Learning (ML) frameworks such as TensorFlow, PyTorch, Caffe / Caffe2, Keras, and MXNet, enables the developers to integrate their favorite AI model / AI framework into products fast and easily.

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