The global AI infrastructure market size is expected to reach USD 197.39 billion by 2030 according to a new study by Polaris Market Research.
The prominent factors for the market growth such as the rising penetration of the cloud machine learning platforms, coupled with the growing focus on parallel computing in artificial intelligence data centers are stimulating the industry demand globally. In addition, increased data traffic and escalating requirements for computing power are further supporting the industry’s development in the forthcoming years. Based on the offering, the hardware segment is holding the highest shares in the global industry in 2020, owing to the demand for artificial intelligence hardware is considerably increasing as of its adoption in various applications such as robotic process automation, machine learning, and biometrics.
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Therefore, businesses are deploying artificial intelligence hardware that creates the demand for AI infrastructure for industry growth worldwide. Whereas the artificial intelligence software and services segment is likely to rise at a healthy rate in the foreseen years due to the growing penetration of digital platforms. Moreover, artificial intelligence applications comprise sparse matrices; video analytics, primitives, inference, and multi-hardware communication ability are boosting the segment growth in impending years.
Growing demand for the Field Programmable Gate Array (FPGA) is an incorporated circuit, which designers or consumers can configure after it is being manufactured (field programmable). These FPGAs are programmed to understand hardware report languages such as Verilog and VHSIC hardware description language (VHDL). FPGAs present various benefits like short time-to-market, fast prototyping, the capability to be redesigned in the domain for long product life, and cycle debugging. This comprises entity programmable logic blocks, generally called configurable logic blocks (CLBs), which are interrelated in that way, users can configure the computing system multiple times. Thus, these features may positively support the artificial intelligence infrastructure industry demand in the near future.
Market participants such as Samsung Electronics, Amazon Web Service, Cadence Design Systems, Cisco, Sensetime, Dell, Xilinx, Graphcore, Advanced Micro Devices, Inc, Hewlett Packard Enterprise Development LP, Google, IBM, Imagination Technologies, INTEL, Micron Technology, Microsoft, NVIDIA, SK Hynix, Tenstorrent, Toshiba, Wave Computing, and Gyrfalcon Technology are some of the key players operating in the global artificial intelligence infrastructure market.
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There are numerous market competitors who are introducing various new products for acquiring a prominent position across the artificial intelligence infrastructure market. For instance, in April 2021, AMD declared that the company is in the process of acquiring Xilinx. The objective of this acquisition is to bring together two industry leaders with complementary product portfolios and capitalize on opportunities in the AI infrastructure industry.
Polaris Market Research has segmented the AI infrastructure market report on the basis of offering, deployment, technology, end-use, and region:
AI Infrastructure, Offering Outlook (Revenue – USD Billion, 2018 – 2030)
- Hardware
- Processor
- Storage
- Memory
- Software
AI Infrastructure, Deployment Outlook (Revenue – USD Billion, 2018 – 2030)
- On-Premises
- Cloud
- Hybrid
AI Infrastructure, Technology Outlook (Revenue – USD Billion, 2018 – 2030)
- Machine Learning
- Deep Learning
AI Infrastructure, End-Use Outlook (Revenue – USD Billion, 2018 – 2030)
- Enterprises
- Government Organizations
- Cloud Service Providers
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