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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