Foxconn, a global leader in smart manufacturing, is joining Socionext, a major provider of advanced SoC solutions for video and imaging systems, and leading artificial intelligence (AI) chipmaker Hailo to launch the next-generation AI processing solution for video analytics at the edge. Foxconn has combined its high-density, fan-less, and highly efficient edge computing solution, "BOXiedge ", with Socionext's high-efficiency parallel processor "SynQuacer " SC2A11, and the Hailo-8 deep learning processor. The new combination provides market-leading energy efficiency for standalone AI inference nodes, benefiting applications including smart cities, smart medical, smart retail, and industrial IoT. In a global AI market forecasted by research firm IDC to approach $98.4 billion in revenue in 2023, this joint solution helps address the need for cost-effective multiprocessing capabilities required in video analytics, image classifications, and object segmentation. The robust, high-efficiency product is capable of processing and analyzing over 20 streaming camera input feeds in real-time, all at the edge.

Needless to say, 8K, 5G and AI rank as some of the major technology trends of the day. However, with a vast number of solutions being rolled out to suit these trends, how to differentiate has become a key element for solutions providers to win out. In this regard, application specific integrated circuit (ASIC)-based systems-on-chips (SoCs), where differentiation is done at the chip level, can help manufacturers design systems and solutions that are truly unique and special, meeting customers' specific requirements. With 5G providing bandwidth 10 times than that for 4G, 8K video is an ideal choice for telecom operators seeking to provide new applications and contents to generate revenue out of their 5G service. Meanwhile, the need for smarter software and algorithms to help end users across verticals achieve further efficiency and business intelligence has triggered demands for AI.

SUNNYVALE, Calif., May 11, 2018 –Socionext Inc., a leading provider of SoC-based solutions, has developed a new Neural Network Accelerator (NNA) engine, optimized for AI processing on edge computing devices. The compact, low power engine has been designed specifically for deep learning inference processing. When implemented, it can achieve 100x performance boost compared with conventional processors for computer vision processing such as image recognition. Socionext will start delivering the Software Development Kit for the FPGA implementation of the NNA in the third quarter of 2018. The company is also planning to develop its SoC products with the NNA.

Yokohama, December 20, 2017 – Socionext Inc., a leader in advanced SoC solution for video and imaging systems, has signed a strategic partnership agreement for the development of an Artificial Intelligence (AI) platform with Silicon Valley, California-based Gyrfalcon Technology Inc. The combination of Gyrfalcon's proprietary AI accelerator chip and Socionext's high-efficiency parallel processor system will create a high-speed, high-density, low-power system to perform image and video analysis, recognition and segmentation in surveillance systems, live-streaming and other video applications. Socionext expects to start sales of the jointly-developed solution with AI capabilities in mid-March, 2018. Turkish electronics maker Bilkon Ltd, which provides surveillance systems for a public agency in Turkey, will be one of Socionext's first customers to apply the AI solution. Requirements for a similar solution are growing, and Socionext and Gyrfalcon will work together to expand the business in the global market.

SUNNYVALE, Calif., April 18, 2017 –Socionext Inc. and SOINN Inc. today announced initial results of collaboration started in 2016, in which Socionext extracts and delivers biometrics data to the "Artificial Brain SOINN". The companies achieved initial results in reading ultrasound images from Socionext's viewphii mobile ultrasound solution by Artificial Brain SOINN. The results will be introduced at Medtec Japan, held in Tokyo Big Sight, April 19-21, at booths 4505 & 4507. In this initial trial, SOINN learned to read subcutaneous fat thickness from abdominal ultrasound images. The estimations by SOINN were then compared with the reading results by ultrasound technicians.