Information Technology
Edge AI Hardware Market worth $58.90 billion by 2030 - Exclusive Report by MarketsandMarkets™
CPUs have the largest market share of processors for edge AI hardware. CPUs' versatility, scalability, and general-purpose nature allow them to process any type of AI task in real time as needed by smart factories, autonomous devices, and industrial IoT applications. CPUs will see mass adoption due to the requirement for on-board computing, which can process large data volumes and execute workloads simultaneously. In other words, CPUs are important processing engines for consumer edge AI platforms and crucial processing engines for enterprise applications requiring on-board computing. CPUs are not as specialized as other processors. They can support a heterogeneous environment of diverse edge applications, whether a smartphone, wearable device, or much more advanced industrial systems, or simple two-factor authentication applications. In short, the adaptiveness and ubiquity of CPUs will ensure that CPUs will be the heavyweight champion of processing units for any edge AI deployment (despite many newer types of processors becoming popular for specialized applications, such as GPUs and ASICs).
Based on several existing technological changes and industry trends, Robots will record the second-highest CAGR in the edge AI hardware market growth over the forecast period. However, as robotics will increasingly combine artificial intelligence (AI) with edge computing, previous examples provided in this report of "edge AI" hybridity will be more likely to accelerate this convergence away from cloud (and hapless potential for near-real-time decision making). Most robots will leverage the growing capacity to process large local data volumes. This will enable robots to make split-second decisions without the caveat of cloud infrastructure. Timely local choices are crucial for autonomous vehicles, industrial automation, and healthcare robotics applications. In many of these applications, milliseconds matter for safety and efficiency. Edge AI decisions made in real time based on large datasets will allow robots to adapt and learn from their increasingly changing surrounding environments rapidly. Robots will also have a better chance of optimizing the dynamic decision-making process with improved accuracy while running advanced machine learning algorithms on the device.
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Asia Pacific has the largest share of the edge AI hardware industry, driven by increased adoption of IoT devices and significant investments in AI-driven technologies in many countries ( China , Japan , South Korea , and India ). Furthermore, the region provides a growing consumer electronics market (smartphone and wearable technology) that requires efficient AI processing, preferably at the edge. Major economies are turning to edge AI applications for smart homes, smart factories, healthcare, and autonomous vehicles. Strong government initiatives and collaborations with leading global technology companies will support the approach. Therefore, with the fastest CAGR and ongoing product and inherent process innovation, the Asia Pacific region is likely to remain ahead in terms of edge AI hardware as it caters to growing industries that value real-time analytics, data privacy, and reduced latency.
Major vendors in the edge AI hardware companies include Qualcomm Technologies, Inc. (US), Huawei Technologies Co., Ltd. ( China ), SAMSUNG ( South Korea ), Apple Inc. (US), MediaTek Inc. ( Taiwan ), Intel Corporation (US), NVIDIA Corporation (US), IBM (US), Micron Technology, Inc. (US), and Advanced Micro Devices, Inc. (US).
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