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市场调查报告书
商品编码
1499361
边缘人工智慧硬体的全球市场:依组件、设备、功耗、流程、产业和地区划分(~2030 年)Global Edge AI Hardware Market Research Report By Component, By Device, By Power Consumption, By Process, By Vertical and By Region -Forecast Till 2030 |
边缘人工智慧硬体市场规模预计将从2024年的32.7501亿美元成长到2032年的159.8785亿美元,预测期内复合年增长率为21.92%。
称为边缘人工智慧的演算法可以在硬体平台上本地处理资料。此功能允许设备自行处理资料并做出决策,而无需连接。AI Accelerator 是一种边缘人工智慧专用硬件,可提高边缘设备的资料密集型深度学习推理能力,使其成为各种运算密集型作业的可行选择。随着即时深度学习工作负载需求的增加,支援快速设备上深度学习的专用边缘人工智慧硬体变得越来越重要。
随着5G和6G网路的融合,边缘AI硬体市场预计将大幅发展。5G网路的引进使得即时、低延迟的边缘AI应用能够无缝部署,增强了AI智慧边缘设备的能力。这些网路还提供超高速连接和高频宽。随着 5G 网路的不断扩展,这些能够在设备密集的环境中进行复杂活动和自主决策的设备预计将会激增。
此外,预计从 2030 年开始开发使用更高频段的 6G 网络,有望实现更快的速度、更多的可用容量和更高的网路可靠性。这些要素对于大规模边缘人工智慧应用至关重要。对强大而有效的硬体解决方案来支援此类尖端网路和应用的需求不断增长,为边缘人工智慧硬体市场的成长创造了有利的环境。
区域展望:
北美被认为是边缘人工智慧硬体市场的最大驱动力。该地区的市场占有率受到大公司存在的影响,这些大公司始终优先考虑併购、产品发布和合作伙伴关係等策略发展,以保持市场竞争力。
亚太地区是全球边缘人工智慧硬体成长最快的市场之一。由于5G的推出和物联网整合设备的增加,亚太地区预计将在边缘人工智慧硬体市场成长排行榜上名列前茅。在中国、日本、印度和韩国,拥有智慧型手机的人数不断增加,人工智慧硬体的市场引入预计将增加。该地区的两个主要市场是中国和日本。汽车、电子和半导体行业的几家领先供应商大力投资人工智慧技术,正在推动该地区边缘人工智慧硬体市场的成长。过去一年,中国边缘人工智慧产业与边缘运算和硬体解决方案相关的发明大幅增加,专利数量证明了中国产业创新的快速发展。
该报告调查了全球边缘人工智慧硬体市场,并提供了市场定义和概述、影响市场成长和市场机会的因素分析、市场规模趋势和预测,并依各个细分市场、地区和主要国家进行了细分。
Global Edge AI Hardware Market Research Report By Component (CPU, GPU, ASIC, and FPGA.), By Device (Smartphone, Camera, Robot, Automobile, Smart Speaker, Wearables, Smart Mirror, and Others), By Power Consumption (into 0-5 W, 6-10 W, and More Than 10 W), By Process (Training and Inference), By Vertical (Consumer Electronics, Smart Home, Automotive & Transportation, Healthcare, Aerospace & Defense, Government, Construction) and By Region (North America, Europe, Asia-Pacific, Middle East and Africa, South America) -Forecast Till 2030
According to projections, the Edge AI Hardware market would expand at a compound annual growth rate (CAGR) of 21.92% from USD 3275.01 million in 2024 to USD 15987.85 million by 2032. An algorithm called Edge AI is capable of locally processing data on a hardware platform. With this feature, a device may process data and make decisions on its own without requiring a connection. AI accelerators are specialized Edge AI hardware that improves Edge devices' ability to do data-intensive deep learning inference, making them a viable choice for various compute-intensive jobs. With the increasing demand for real-time deep learning workloads, specialized Edge AI hardware that enables fast deep learning on the device has become increasingly crucial.
The market for edge AI hardware is expected to develop significantly as a result of the 5G and 6G networks being integrated. The introduction of 5G networks has allowed for the seamless deployment of real-time, low-latency Edge AI applications, hence increasing the capabilities of AI-enabled intelligent edge devices. These networks also offer ultra-fast connectivity and high bandwidth. The market can anticipate a proliferation of these devices capable of complicated activities and autonomous decision-making in surroundings with a high density of devices as 5G networks continue to expand.
Furthermore, even faster speeds, more available capacity, and improved network dependability are promised by the development of 6G networks, which are expected to be developed after 2030 and use higher frequency bands. These factors are essential for Edge AI applications on a big scale. Because of the increasing need for strong and effective hardware solutions to support these cutting-edge networks and applications, this presents a favorable environment for the growth of the Edge AI hardware market.
insights on market segments
The Edge AI Hardware Market is divided into four segments based on component: CPU, GPU, ASIC, and FPGA.
The Edge AI Hardware Market is divided into categories based on devices, including wearables, smart mirrors, smartphones, cameras, robots, cars, and others.
The Edge AI Hardware Market is divided into three segments based on power consumption: 0-5 W, 6-10 W, and More.
The consumer electronics, smart home, automotive & transportation, healthcare, aerospace & defense, government, construction, and other segments make up the Edge AI Hardware Market, according to Vertical.
Localized Perspectives
The market for Edge AI Hardware is probably most driven by North America. The US, Canada, and Mexico are included in this. The presence of large corporations that constantly prioritize strategic development-mergers, acquisitions, product launches, partnerships-in order to maintain their competitiveness in the market has an impact on the regional market share. For instance, in September 2021, Synaptics Inc. and Edge Impulse forged a partnership. With this cooperation, thousands of embedded developers will have access to Synaptics' KatanaUltra Low-Power Edge AI Platform and the Edge Impulse software development platform, enabling them to create, train, and implement custom models for a variety of AI applications.Developers may create models that are ready for production more quickly and efficiently with the help of the Edge Impulse Embedded ML Platform. Additionally, it simplifies model training, testing, and optimization in the context of comprehensive MLOps.
One of the world's fastest-growing markets for Edge AI hardware is Asia Pacific. The Asia Pacific region is expected to soar to the top of the Edge AI Hardware Market growth chart due to the deployment of 5G in the area and the increase in IoT-integrated devices. The increasing number of people in China, Japan, India, and South Korea who own smartphones is expected to increase the market adoption of AI hardware. The two largest markets in the area are China and Japan. The presence of multiple large suppliers in the automotive, electronics, and semiconductor industries that are making significant investments in AI technology is fueling the growth of the edge AI hardware market in the region. China's edge AI industry has seen tremendous increase in invention over the past year for edge computing and hardware solutions, as evidenced by the number of patents issued, highlighting the nation's rapid industrial innovation.
Principal Players
The leading players in the market are NVIDIA Corporation, ARM, Hailo, MediaTek Inc., Xilinx Inc., Micron Technology, Apple Inc., Qualcomm Incorporated, Huawei Technologies Co., Ltd., Intel Corporation, NVIDIA Corporation, Samsung Electronics Co., Ltd., and IBM Corporation.