The Artificial intelligence (AI) refers to the theory
and development of computer systems capable of performing tasks that usually
require human intelligence. AI involves the study and synthesis of intelligent
agents—in this case, a computer system. AI applications process large volumes of
data, and they require powerful processing capabilities outside. AI
infrastructure enables superior data throughput and storage capacity, as well
as large data workloads.
AI infrastructure comprises hardware components such as processors, memory, storage devices, and networking, as well as server software. All these components deliver higher performance and improved efficiency than that of the conventional components. AI-optimized solutions can learn the patterns, relationships, transformations on their own when the data is shown to machine learning algorithms. The global AI infrastructure market is projected to grow from USD 14.6 billion in 2019 to USD 50.6 billion by 2025, at a CAGR of 23.1%.
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Key Players:
Key players operating in the AI infrastructure market are Intel Corporation (US), NVIDIA Corporation
(US), IBM (US), Samsung Electronics (South Korea), Google (US), Microsoft (US),
Micron Technology (US), Amazon Web Services (US), CISCO (US), Oracle (US), ARM
(UK), Xilinx (US), Advanced Micro Devices (AMD) (US), Dell (US), HPE (US),
Habana Labs (Israel), and Synopsys Inc. (US). Increasing adoption of cloud
machine learning platform and escalating demand for AI hardware in
high-performance computing data centers are driving the AI infrastructure
market.
The AI infrastructure market for the hardware segment is estimated
to grow at the highest CAGR during the forecast period
The AI
infrastructure market based on hardware has been further segmented into a
processor, memory, storage, and networking (switches, routers, and other
equipment used to link servers in the cloud and to connect edge devices).
NVIDIA (US), Intel (US), Micron (US), Xilinx (US), Google (US), Samsung (South
Korea), Habana Technologies (Israel), and Graphcore (UK) are a few of the
companies that develop hardware needed for AI.
The AI infrastructure market for deep learning is expected to grow
at the highest CAGR during the forecast period
Deep learning is a
class of ML based on multiple algorithms for creating relationships among data.
Deep learning uses artificial neural networks to learn a representation of
multiple levels of data, such as texts, images, and sounds. Its algorithms help
in identifying patterns from a set of unstructured data. Presently, deep
learning technology is used in voice recognition, fraud detection,
recommendation engines, sentiment analysis, image recognition, motion
detection, etc. Algorithms help in identifying patterns from a set of
unstructured data. Deep learning uses artificial neural networks to learn
multiple levels of data.
The AI infrastructure market for inference function is estimated
to grow at a higher CAGR during the forecast period
Inference is sensitive to latency, and the trained model needs to analyze and provide analysis in near real time. The requirement of the infrastructure for model deployment to accelerate the data at the fastest rate is expected to drive the market for inference.
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Among all regions, the market in APAC is expected to witness the
highest CAGR during the forecast period
The market in APAC mainly constitutes major economies such as Singapore, South Korea, Japan, China, India, and Australia, which are expected to register high growth in the AI infrastructure market. 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.
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