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市場調查報告書
商品編碼
1499361
邊緣人工智慧硬體的全球市場:依組件、設備、功耗、流程、產業和地區劃分(~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 |
邊緣人工智慧硬體市場規模預計將從2024年的32.7501億美元成長到2032年的159.8785億美元,預測期內複合年增長率為21.92%。
稱為邊緣人工智慧的演算法可以在硬體平台上本地處理資料。此功能允許設備自行處理資料並做出決策,而無需連接。AI Accelerator 是一種邊緣人工智慧專用硬件,可提高邊緣設備的資料密集型深度學習推理能力,使其成為各種運算密集型作業的可行選擇。隨著即時深度學習工作負載需求的增加,支援快速設備上深度學習的專用邊緣人工智慧硬體變得越來越重要。
隨著5G和6G網路的融合,邊緣AI硬體市場預計將大幅發展。5G網路的引進使得即時、低延遲的邊緣AI應用能夠無縫部署,增強了AI智慧邊緣設備的能力。這些網路還提供超高速連接和高頻寬。隨著 5G 網路的不斷擴展,這些能夠在設備密集的環境中進行複雜活動和自主決策的設備預計將會激增。
此外,預計從 2030 年開始開發使用更高頻段的 6G 網絡,有望實現更快的速度、更多的可用容量和更高的網路可靠性。這些要素對於大規模邊緣人工智慧應用至關重要。對強大而有效的硬體解決方案來支援此類尖端網路和應用的需求不斷增長,為邊緣人工智慧硬體市場的成長創造了有利的環境。
區域展望:
北美被認為是邊緣人工智慧硬體市場的最大驅動力。該地區的市場佔有率受到大公司存在的影響,這些大公司始終優先考慮併購、產品發佈和合作夥伴關係等策略發展,以保持市場競爭力。
亞太地區是全球邊緣人工智慧硬體成長最快的市場之一。由於5G的推出和物聯網整合設備的增加,亞太地區預計將在邊緣人工智慧硬體市場成長排行榜上名列前茅。在中國、日本、印度和韓國,擁有智慧型手機的人數不斷增加,人工智慧硬體的市場引入預計將增加。該地區的兩個主要市場是中國和日本。汽車、電子和半導體行業的幾家領先供應商大力投資人工智慧技術,正在推動該地區邊緣人工智慧硬體市場的成長。過去一年,中國邊緣人工智慧產業與邊緣運算和硬體解決方案相關的發明大幅增加,專利數量證明了中國產業創新的快速發展。
該報告調查了全球邊緣人工智慧硬體市場,並提供了市場定義和概述、影響市場成長和市場機會的因素分析、市場規模趨勢和預測,並依各個細分市場、地區和主要國家進行了細分。
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.