The efficient implementation of in-home health monitoring and health information access; personalized health management; and the use of treatment devices (such as better hearing aids; visual assistive devices; and physical assistive devices that include intelligent walkers) are possible with the implementation of AI-based tools. Thus, there is a growing focus on adopting AI-based technologies to support the physical, emotional, social, and mental health of the elderly population across the world. Future applications may include a combination of multiple AI technologies, such as ML, DL, and computer vision, for pose detection and learning elderly behavioral patterns.
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Based on the technology, the AI infrastructure market has been divided into machine learning and deep learning. In terms of value, deep learning technology is expected to account for a larger share of the AI infrastructure market by 2026. The ability of deep learning to collect and handle big data and its applications in autonomous robots, autonomous vehicles, and facial analysis is fueling its demand. These technologies are currently being implemented to develop various AI products and offer different kinds of services. AI has created significant opportunities for enterprises, cloud service providers, thereby helping many startups to provide their solutions in the AI infrastructure market.
On the basis of end user, the market is categorized into enterprises, government organizations, and cloud service providers. Cloud service providers are expected to account for the largest share of the AI infrastructure market, by end user, by 2026. Cloud services drive cost-saving and supporting digital business transformation. Hence, the adoption of cloud services is high in the AI infrastructure space.
Among all regions, APAC is expected to register the highest growth in the AI infrastructure market during the forecast period. The AI infrastructure market in APAC includes economies such as Singapore, South Korea, Japan, China, India, and Australia. APAC is the host to a few of the fastest-growing and leading industrialized economies such as China, Japan, and India in the world. It is witnessing dynamic changes in the adoption of new technologies and advancements in organizations across industries. Increasing adoption of deep learning and NLP technologies for finance, agriculture, marketing, and law applications is also driving the market in this region.