Monday, June 17, 2024

Compact Computing Device for AI Edge Inference

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ASUS IoT has introduced next-generation computing device with highly efficient and powerful GPU for AI-powered IoT applications.


ASUS IoT, has launched PE1100N, which the company claims to be an extraordinary, ultra-compact computing device designed for Artificial Intelligence (AI) inferencing at the edge. The device is based on the next-generation cutting-edge NVIDIA Jetson Orin series. Boasting a fanless design, it ensures silent operation, while its robust industrial connectivity offers flexibility. According to the press release issued by the company, with support for a wide range of power inputs and operating temperatures, the device guarantees exceptional versatility and durability.

The company claims that the cutting-edge computing solution is powered by the Jetson platform’s efficient ARM processor and embedded NVIDIA GPU. This remarkable combination enables energy-efficient computing while delivering powerful AI-inferencing capabilities. Its versatility makes it an excellent choice for a wide range of edge AI applications in smart cities, transportation, and manufacturing. The device excels in diverse and scalable edge AI deployments, from traffic analysis to people tracking, counting, and surveillance. Furthermore, its compact size and anti-vibration design make it particularly well-suited for smart manufacturing solutions, including automated guided vehicles (AGVs), autonomous mobile robots (AMRs), AI-powered automated optical inspection (AOI), and robotics applications. By using this device, businesses can accelerate their time to market for AI applications and unlock the full potential of their automation initiatives.

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The fanless and rugged device incorporates a unique metal heatsink and an extruded aluminium chassis. The design ensures efficient and silent cooling, allowing for stable and reliable operation even in extreme temperatures ranging from -20°C to 50°C. The press release highlights the device has an impressive capability of delivering up to 100 trillion operations per second (TOPS) and operating on low power (10-25 W). The device enables efficient deep learning and computer vision tasks. Compared to previous-generation devices, it offers up to 5 times the performance while consuming significantly less power. Additionally, it achieves up to 18 times better frames-per-watt efficiency than traditional x86-based platforms. Furthermore, the device allows developers to execute AI and machine learning models using readily available SDK and library tools.

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Nidhi Agarwal
Nidhi Agarwal
Nidhi Agarwal is a journalist at EFY. She is an Electronics and Communication Engineer with over five years of academic experience. Her expertise lies in working with development boards and IoT cloud. She enjoys writing as it enables her to share her knowledge and insights related to electronics, with like-minded techies.


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