Edge AI Hardware Market Size Estimation 2019 | Technological Advancement, Application Analysis and Regional Outlook Forecast to 2025

On the basis of processors, the edge AI hardware market can be segmented into CPU, GPU, and ASIC. CPU is the most commonly used processor for computers, smartphones, and wearables. CPU used for edge AI smartphones are Snapdragon 845 and 855 from Qualcomm, A11 and A12 bionic chips from Apple, Exynos 9820 from Samsung, and Kirin 980 from Huawei. ASIC has the ability of only one dedicated operation due to which the entire chip is dedicated to a set of narrow functions. This makes it capable of performing tasks at a very high speed. GPU is a processor with a single chip processor basically used to boost the performance of video graphics. It has thousands of cores, which make it able to handle thousands of software simultaneously. GPU has achieved this power while reducing the cost of operations.

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On the basis of power consumption, edge AI hardware market can be segmented into five types, four of which are less than 1 W, 1-3 W, 3-5 W, and 5-10 W and one of which is more than 10 W. The steady increase in the demand for real-time voice and speech synthesis and recognition along with technological developments in smartphone image recognition is the driver for the AI hardware market. Most of the AI processors have preprogrammed Neural Processing Units (NPUs), that handle substantial amounts of parallel data processing using low power. Most of the AI-related work detection, pattern matching, and prediction are being carried out primarily in the cloud. With AI processors built in a smartphone, tasks can be carried out on the device itself without any connectivity. This will improve the performance of the device and reduce strain on battery usage.

The increasing amount of data from all sectors is raising a problem of operational and storing cost of that data. All storage equipment manufacturers are investing in R&D to develop devices, which can store more data in less space and are cost-effective. AI hardware can store this big amount of data on the cloud so that the physical storing space can be saved and data can be accessed globally. The processing of a big amount of data is also a tricky task that can be solved by developing and using devices, which can take decisions on their own. Edge AI hardware has the ability to take the data process and decisions accordingly so that the storage and processing problem can be solved.

Some of the key players in the Edge AI Hardware market are Microsoft Corporation, Google, Samsung Electronics Corporation Ltd., Huawei Technologies Corporation Ltd., MediaTek Inc., Imagination Technologies Ltd., NVIDIA Corporation, and Xilinx Inc.

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The North America market is anticipated to hold the largest share in the edge AI hardware market due to the increasing number of IoT-dependent devices, internet network congestion, high latency, and the need for developing fast data processing devices. The working of surveillance cameras and drones that is mostly based on VPU (Virtual Processing Unit) is expected to grow significantly in this region. North America is a hub for many prominent technology players, such as Google, Microsoft, and IBM, which will help this market to grow.

In the Asia Pacific region, China and Japan are expected to hold the largest edge AI hardware market share due to the presence of a large number of manufacturing firms and strong production of semiconductors, automobiles, and electronics. These countries also have a huge growth potential in smartphones, automobiles, and industrial robotics. With the growing usage of smartphones in countries including China, India, Japan, and South Korea, the adoption of AI processor-enabled smartphones is anticipated to increase over the forecast period. Asia Pacific is one of the largest markets for industrial robotics, wearable devices, and surveillance cameras, which all are integrated with AI to improve the speed and accuracy of devices.

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