The global AI in the infrastructure market is anticipated to grow significantly at a CAGR of 26.8% during the forecast period (2021-2027). The increase in need and demand for the effective managing, storing, and interpretation of the data is expected to accelerate the implementation of AI in infrastructure across the globe. According to the Cisco Systmes, Inc. report published in December 2020, the global internet protocol (IP) traffic is expected to reach around 1.2 zeta bytes per month and 3.3 zeta bytes per year in 2021. Thus, the data reported signifies that IP traffic globally is likely to flourish generate more chunks of data in the coming years, which further raises the need for higher computing power devices across the data centers.
Browse the full report description of "Global AI in Infrastructure Market Size, Share & Trends Analysis Report by Offering (Hardware and Server Software), by Technology (Machine Learning and Deep Learning), by Function (Training and Inference), by Deployment Mode (On-Premise, Cloud-Based, and Hybrid), and by End-User (Cloud Service Provider, Enterprise, and Government Organizations) Forecast Period, 2021-2027" at https://www.omrglobal.com/industry-reports/ai-in-infrastructure-market
Further, a high processing computer-intensive chip plays a very crucial role in processing AI algorithms faster to process the data required more quickly as compared to traditional processing methods for creating effective AI systems. Presently, AI chips are used in high-end servers and data centers that don't have enough power and are not capable of handling huge data or workloads. Hence, the key industry players are focusing on developing a broad range of GPU memory bandwidth depending on the application. For instance, in June 2019, General Electric Force launched GTX Titan to provide improved memory bandwidth of 336.5 Gigabytes per second. The new GPU developed can only be deployed on desktops and PCs. Furthermore, in 2020, Tesla, a manufacturing giant for EVs incorporated GPU offering 900 Gigabyte memory bandwidth in its Tesla V100 16 GB. Additionally, the processor developed has been considered the most suitable for AI applications.
Market Coverage
o By Offering
o By Technology
o By Function
o By Deployment Mode
o By End-User
o North America
o Europe
o Asia-Pacific
o Rest of the World
Key questions addressed by the report
o Deviation from the pre-COVID-19 forecast
o Most affected region and segment
Global AI in Infrastructure Market – Segmentation
By Offering
o Processor
o Memory
o Storage
o FPGA
By Technology
By Function
By Deployment Mode
By End-User
Global AI in Infrastructure Market – Segmentation by Region
North America
Europe
Asia-Pacific
Rest of the World
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