Global Edge AI Hardware Market: Emergence of AI Coprocessors for Edge Computing is Boosting the Market Growth

Edge AI Hardware Market

In Edge AI, on a hardware device, the AI algorithms are processed locally without any connection. It uses information produced from the system and analyses it in less than a few milliseconds to provide real-time insights. Such hardware components, including processors, sensors, cameras, etc., are used to incorporate and enhance the functionality of these AI devices by storing the data in the device itself without cloud systems or cloud computing being needed.  This artificial intelligence in edge helps them to be highly responsive, enhance customer experience, and provide security. Compared to hierarchical IoT models, Edge AI enabled devices to process data very quickly. Some of the common Edge AI hardware devices are smart speaker, cameras, smartphone, robots, smart mirror among others.

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Some of the factors responsible for the growth of this Edge AI Hardware Market are:

  • Emergence of AI Coprocessors for Edge Computing: Edge computing is a computational methodology used to bring decision-making closer to the data source and artificial intelligence is a computer science discipline that seeks to create smart devices. With the integration of artificial intelligence with edge computing technologies they can widely be used in many applications and can meet the requirement of other technologies such as Internet of Things. In order to create devices capable of deep learning, portable AI coprocessors could be built into boards. Using these systems also helps in decreasing the maintenance cost
  • Rapid Growth in the Number of Edge Computing Products and Services: Edge computing is a decentralized, open IT system with shared processing power which enables mobile computing and IoT technologies. It allows acceleration of the data stream, including the processing of data in real time without latency. It enables intelligent applications and devices to respond to data almost instantly by reducing the delays.       They have ability to allow efficient data processing and decrease the decrease in Internet bandwidth usage. Some of the benefits of the edge computing are enhanced speed, efficiency & security, scalability & versatility among others

The global edge AI hardware market is segmented on the basis of device as smartphones, cameras, robots, wearables, smart speaker, automotive, and smart mirror; processors as cpu, gpu, asic, others; power consumption as less than 1w, 1-3w, 3-5w, 5-10w, and more than 10w; process training & inference and end-user industry as consumer electronics, smart home, automotive & transportation, government, healthcare, industrial, aerospace & defense, construction, others

Some of the launches and acquisition in the Edge AI Hardware Market are:

  • In May 2019, NVIDIA Corporation announced the launch of NVIDIA EGX. It is specially designed to meet the growing demand for immediate, high-throughput AI quality at the edge, where data is generated with guaranteed response times, while reducing the amount of data to be sent to the cloud. This new platform will help them to easily deploy systems so they can meet their requirement in both cloud and on- premises
  • In September 2019, Edgise announced that they are going to develop custom hardware for AI computing at the edge. This solution has many advantages, particularly apeedy, consistency and confidentiality benefits, over the cloud. Through bringing the information to the edge, Edgise is planning to reduce reaction times, enable quicker applications, and reduce privacy risks

According to Data Bridge Market Research, global edge AI is set to witness a healthy CAGR of 20.27% in the forecast period of 2019-2026

Few of the major competitors currently working in edge AI hardware market are videantis GmbH; Qualcomm Technologies, Inc.; NVIDIA Corporation; Premier Farnell Limited; Micron Technology, Inc.; Alphabet Inc.; SecureRF Corporation; Microsoft; Xilinx Inc.; Intel Corporation; Huawei Technologies Co., Ltd.; SAMSUNG; Apple Inc.; Arm Limited; MediaTek Inc.; Applied Brain Research, Inc.; Horizon Robotics; Cadence Design Systems, Inc.; CEVA, Inc.; Imagination Technologies Limited; Synopsys, Inc.; Thinci; General Vision; Mythic; Adapteva, Inc.; Tenstorrent Inc and VeriSilicon Limited

Growing demand for faster and more powerful hardware devices in AI applications that require lower processing time will accelerate the market growth. Rising availability of dedicated AI processor for on- device image analytics will also enhance the market growth. Increasing prevalence of edge computing in IoT is another factor which is positively impacting the market growth.

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