Artificial intelligence is gaining traction across various platforms, necessitating infrastructure that allows effective and efficient workflows. A well-developed AI infrastructure aids scientists and developers in accessing data, deploying machine learning algorithms, and managing hardware’s computing resources efficiently. AI infrastructure makes use of AI and machine learning (ML) to develop and deploy reliable data solutions.
The growing volume of data and the rising complexity of ML models are aiding the AI infrastructure market growth. Robust AI infrastructure has the potential to scale up to the data growth, allowing businesses to handle future requirements.
Globally, with the rising volumes of data, safety and security concerns pertaining to data privacy and regulatory requirements are on the rise. AI infrastructure aids in ensuring compliance with laws and standards, thereby reducing potential legal and reputational risks.
Increasing partnerships between key players for the development of AI infrastructure are favouring the market growth. For instance, in December 2023, Malaysian conglomerate YTL announced its partnership with Nvidia Corporation (NASDAQ: NVDA) to develop artificial intelligence (AI) infrastructure in the country.
The AI infrastructure is slated to be hosted in the data centre located in the southern state of Johor. Through the deal, the companies aim to develop supercomputers using Nvidia AI chips and with YTL Power International, making use of Nvidia's AI cloud computing platform to develop a large language model in Malaysia.
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Market Analysis by Type, Technology, Deployment, Function, End Use, and Region:
- The market, on the basis of type, can be divided into hardware and server software.
- Based on technology, the market can be divided into machine learning and deep learning.
- Based on deployment, the market can be classified into on premise, cloud, and hybrid.
- The various functions of AI infrastructure include training and inference.
- The different end uses of AI infrastructure are enterprises, government organisations, and cloud service providers.
- The major regional markets for AI infrastructure include North America, Europe, the Asia Pacific, Latin America, and the Middle East and Africa.
Key Findings of the Report:
- The rising concerns regarding the safety and security of data are propelling the AI infrastructure market expansion.
- The growing volume of data generation is surging the requirement for AI infrastructure to ensure improved performance and reliability.
- Transition towards cloud storage systems across various end-use sectors, including healthcare, is contributing to an increased establishment of AI infrastructure.
- The rising use of multicore processors and GPUs is catering to the greater importance of parallel computing, further supporting market growth.
Key Offerings of the Report:
- The EMR report gives an overview of the global AI infrastructure market for the periods (2018-2023) and (2024-2032).
- The report also offers the historical (2018-2023) and forecast (2024-2032) markets for the types, technologies, deployments, functions, end uses, and major regions of AI infrastructure.
- The report analyses the market dynamics, covering the key demand and price indicators in the market, along with an assessment of the SWOT and Porter’s Five Forces models.
The major players in the global AI infrastructure market are Intel Corporation, Nvidia Corporation, Google LLC, Microsoft Corporation, Cisco Systems, Inc., Amazon Web Services, Inc., International Business Machines Corporation, and Arm Limited, among others. The comprehensive report by EMR looks into the market share, capacity, and latest developments like mergers and acquisitions, plant turnarounds, and capacity expansions of the major players.
Key Highlights of the Report
| REPORT FEATURES |
DETAILS |
| Base Year |
2023 |
| Historical Period |
2018-2023 |
| Forecast Period |
2024-2032 |
| Scope of the Report |
Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment:
- Type
- Technology
- Deployment
- Function
- End Use
- Region
|
| Breakup by Type |
|
| Breakup by Technology |
- Machine Learning
- Deep Learning
|
| Breakup by Deployment |
|
| Breakup by Function |
|
| Breakup by End Use |
- Enterprises
- Government Organizations
- Cloud Service Providers
|
| Breakup by Region |
- North America
- Europe
- Asia Pacific
- Latin America
- Middle East and Africa
|
| Market Dynamics |
- SWOT Analysis
- Porter's Five Forces Analysis
- Key Indicators for Demand
- Key Indicators for Price
|
| Competitive Landscape |
- Market Structure
- Company Profiles
- Company Overview
- Product Portfolio
- Demographic Reach and Achievements
- Certifications
|
| Companies Covered |
- Intel Corporation (NASDAQ: INTC)
- Nvidia Corporation (NASDAQ: NVDA)
- Google LLC
- Microsoft Corporation (NASDAQ: MSFT)
- Cisco Systems, Inc. (NASDAQ: CSCO)
- Amazon Web Services, Inc.
- International Business Machines Corporation (NYSE: IBM)
- Arm Limited
- Others
|
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