AI in hardware Global Market Growth Analysis, Industry Insights, Outlook 2023 To 2032

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The AI In Hardware Global Market Report 2023 by The Business Research Company, provides ai in hardware market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa for the 27 major global industries. The report covers a ten-year historic period – 2010-2021, and a ten-yearforecast period – 2023-2032.

 

Learn More On The AI In Hardware Market:
https://www.thebusinessresearchcompany.com/report/ai-in-hardware-global-market-report

According to The Business Research Company’s AI In Hardware Global Market Report 2023, the market size is expected to grow from$16.82 billion in 2022 to $20.88 billion in 2023 at a compound annual growth rate (CAGR) of 24.14%. The Russia-Ukraine war disrupted the chances of global economic recovery from the COVID-19 pandemic, at least in the short term. The war between these two countries has led to economic sanctions on multiple countries, a surge in commodity prices, and supply chain disruptions, affecting many every market across the globe. The global AI in hardware market size is expected to reach $48.18 billion in 2027 at a CAGR of 23.25%.The adoption of AI hardware in banking, IT, and telecom is expected to propel the growth of the AI in hardware market going forward. Banking, IT and telecom are all growing industries. These industries are increasingly leveraging AI technologies to enhance their operations, improve customer experiences, and drive innovation. AI hardware is used in banking to enhance fraud detection and prevention, risk management, and customer service. IT companies use AI hardware to analyze large amounts of data from connected devices to detect anomalies and predict when maintenance is required and telecom companies use AI-enabled hardware to analyze network traffic in real-time to identify and fix performance issues.

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The ai in hardware market is segmented:

1) By Type: Processor, Network, Storage
2) By Deployment: Cloud, On-Premise
3) By Technology: Machine Learning, Computer Vision, Natural Language Processing, Expert Systems
4) By Application: Training And Simulation, Driver Monitoring Systems, Surveillance And Security, Imaging And Diagnosis, Robotic Surgery
5) By End User: Telecommunication And IT industry, Banking And Finance Sectors, Education, Ecommerce, Navigation, Robotics, Agriculture, Health care
Technological advancements are the key trends gaining popularity in the AI in hardware market. Major companies operating in the AI in hardware market are adopting new technologies to sustain their position in the market. For instance, in April 2021, Intel Corporation, a US-based semiconductor technology corporation, launched 3rd generation Intel Xeon Scalable processors with built-in artificial intelligence (AI) acceleration. This innovative technology, combined with Intel’s portfolio of Ethernet adapters, FPGAs, persistent memory and storage, Intel® OptaneTM, optimized software solutions, high-performance computing (HPC), networking, and intelligent edge applications, enables performance and workload improvements. Additionally, include features such as vector neural network instructions (VNNI), which accelerate convolutional neural networks, and tensor float 32 (BFLOAT16) support, which speeds up training and inference in deep learning models. With these AI acceleration capabilities, the 3rd generation Intel Xeon Scalable processors are well-suited for use in AI and machine learning applications.

 

The ai in hardware market report table of contents includes:
1. Executive Summary
2. AI In Hardware Market Characteristics
3. AI In Hardware Market Trends And Strategies
4. AI In Hardware Market – Macro Economic Scenario
5. COVID-19 Impact On AI In Hardware Market
……………………………..
26. Africa AI In Hardware Market
27. AI In Hardware Market Competitive Landscape And Company Profiles
28. Key Mergers And Acquisitions In The AI In Hardware Market
29. AI In Hardware Market Future Outlook and Potential Analysis
30. Appendix

 

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