Leopard is working with Hailo, an AI chipmaker for edge devices, Socionext, a developer of advanced system-on-chip (SoC) solutions for imaging and video systems; and Amazon Web Services (AWS) to launch this transformative solution.
The venture looks to produce high image quality and high energy efficiency for AI inference nodes, benefiting a wide range of applications in industrial automation, smart devices, smart retail, and others.
Leopard Imaging has been working to address the need for affordable multiprocessing power in deep learning applications. Using Socionext’s SC2000 image signal processor and the Hailo-8 M.2 AI acceleration module, the EdgeTuring consumes less power, performs at a higher level, and ensures greater reliability for video analytics and privacy at the edge than alternative solutions.
By leveraging AWS services such as Amazon Kinesis Video Streams and Amazon Kinesis Data Streams (Amazon KDS), EdgeTuring is capable of creating a seamless experience for customers to stream and analyze videos using a simple internet connection.
"EdgeTuring has an accuracy ranging from 95% to 99% for several state-of-the-art deep learning-based computer vision applications, such as object detection, image classification and others. Additionally, it processes frames much faster, supports more functions, consumes less power, and costs much less than any comparable solution - all with the ability to stream inputs in real-time," said Bill Pu, President and Co-Founder of Leopard Imaging. "We believe that this strategic collaboration will help us carve a new path forward in the AI-driven camera industry. We want to break away from the status quo and embrace these opportunities to adopt new AI solutions.”
The Hailo-8, launched last year, makes it possible to integrate high performance AI capabilities of 26 Tera Operations Per Second (TOPS) into edge devices, providing a more flexible solution for accelerating a wide range of deep learning-based applications.
