Edge AI Hardware Market Size, Industry Analysis Report, Regional Outlook, Growth Potential, Competitive Market Share & Forecast, 2019-2025
Report ID: GMI3424
Edge AI Hardware Market size is anticipated to grow substantially during the forecast period with the increasing demand for real-time processing and the use of low-latency devices. Edge AI is an algorithm, which can process the data locally on a hardware device. This ability makes a device capable of processing data and takes decisions independently without being connected. The increasing demand for self-driving cars, advanced healthcare equipment, and robotics where real-time automatic decision-making machines are gaining importance will increase the demand for the edge AI hardware market.
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.
The AI system relies completely on the cloud as it comes with the capacity to serve a limited number of connections and availability irrespective of whether that connection is from a cellular network, wired LAN or Wi-Fi. It typically takes at least 10 milliseconds. Edge devices use data inputs to avoid network delays entirely. This task can start in microseconds and the device can start responding as soon as the answer is ready rather than waiting for the answer to come back from the cloud. This will help camera, robots, edge gateways, and devices to make better decisions and judgments without connecting to the phone for any inquiry or assistance.
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.
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 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 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.
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.
Edge AI Hardware Market, By Processors, 2014-2025 (USD Million)
Edge AI Hardware Market, By Device, 2014-2025 (USD Million)
- Smart speakers
- Smart Mirrors
Edge AI Hardware Market, By Power Consumption, 2014-2025 (USD Million)
- Less than 1 W
- 1 to 3 W
- 3 to 5 W
- 5 to 10 W
- More than 10 W
Edge AI Hardware Market, By Processor, 2014-2025 (USD Million)
Edge AI Hardware Market, By End User, 2014-2025 (USD Million)
- Consumer electronics
- Smart home
- Automotive and transportation
- Aerospace and defense
The above information has been provided for the following regions and countries:
- North America
- Australia & New Zealand (ANZ)
- South Korea
- Latin America
- South Africa
- Saudi Arabia
- Applied Brain Research
- Horizon Robotics
- Huawei Technologies Corporation Ltd.
- Imagination Technologies Ltd.
- Intel Corp.
- MediaTek Inc.
- Micron Technology
- Microsoft Corporation
- NVIDIA Corporation
- Qualcomm Inc.
- Samsung Electronics Corporation Ltd.
- Securerf Corporation
- Synopsys Inc
- Xilinx Inc.
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