The artificial intelligence chipsets market size is estimated to grow from USD 7.2 Billion in 2020 to USD 80.6 Billion by 2027, growing at a CAGR of 41.2% during the forecast year from 2021 to 2027.
Artificial intelligence chips are silicon chips, which slot in artificial intelligence technology and are indulged with machine learning. AI supports in minimizing the risk to human life in numerous industry verticals. The emergence of quantum computing and increase in adoption of AI chips in robotics boosts the growth of the artificial intelligence chip market globally.
The artificial intelligence chipsets market is bifurcated into product, technology, end-user and region. The deep learning, sub-segment of technology is capable of unsupervised learning from unstructured data. Deep learning has been considered as an alarming tool for enterprises that require actionable insights and facilitate automated responses to bulky unstructured data. Many of the highly developed automation found in enterprise artificial intelligence platforms is recognized for the growth and adoption of machine learning and deep learning.
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The North America region is anticipated to witness highest market share during the forecast period. The region was accounted for more than 40.0% share during the base year, due to a large number of major players based in the U.S. for AI chipset. The research covers the current and historic artificial intelligence chipsets market size and its growth trend with company outline of Key players/manufacturers: Google, Samsung Electronics, Microsoft, Micron Technology, Qualcomm Technologies, Intel, Amazon Web Services (AWS), IBM, Nvidia, and Xilinx among others.
The artificial intelligence chipsets market research report provides an in-depth overview of the industry including market segmentation by product, technology, end-user and geography. Analysis of the global market with special focus on high growth application in each vertical and fast-growing market segments. It includes detailed competitive landscape with identification of the key players with respect to each type of market, in-depth market share analysis with individual revenue, market shares, and top players rankings. Impact analysis of the market dynamics with factors currently driving and restraining the growth of the market, along with their impact in the short, medium, and long-term landscapes. Competitive intelligence from the company profiles, key player strategies, game-changing developments such as product launches and acquisitions.
The objective of this study is to identify the market opportunities and estimate market size by segments and countries for last few years and to forecast the values to the next five years. The report incorporates both the qualitative and quantitative aspects of the industry with respect to each of the regions and countries involved in the study. The report also covers qualitative analysis on the market, by incorporating complete pricing and cost analysis of components & products, Porter’s analysis and PEST (Political, Economic, Social & Technological factor) analysis of the market. The report also profiles all major companies active in this field.
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Market Analysis and Insights: Artificial Intelligence Chipsets Market Analysis & Insights
Artificial Intelligence Chipsets Market Scope and Market Size
Artificial intelligence chipsets market is segmented by region and further by countries, product, technology, and end-user. Players, stakeholders, and other participants in the global artificial intelligence chipsets market will be able to gain a strong position as this report will surely benefit their marketing strategies. The market analysis focuses on revenue and forecast by region/countries and by application in terms of revenue and forecast for the period 2016-2027.
Report further studies the market development status and future and Artificial Intelligence Chipsets Market trend across the world. Also, it splits artificial intelligence chipsets market segmentation by product, technology, end-user and region to deep dive research and reveals market profile and prospects.
Major Classifications are as follows:
- Graphics processing unit (GPU)
- Application Specific Integrated Circuit (ASIC)
- Central Processing Unit (CPU)
- Field-Programmable Gate Array (FPGA)
- Natural Language Processing (NLP)
- Robotic Process Automation (RPA)
- Computer vision
- Network security
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforced Learning
- Unsupervised Learning
- Media & advertising
- Consumer electronics
- IT & Telecom
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