AI Chipsets Market

The report "AI Chipsets Market by Hardware (Processor, Memory, Network), Technology (Machine Learning, Natural Language Processing, Computer Vision), Function (Training, Interference), End-User Industry and Region - Global Forecast to 2028" The AI Chipsets  market is projected to grow from USD 51.2 billion in 2023 and is estimated to reach USD 131.8 billion by 2028; it is expected to grow at a Compound Annual Growth Rate (CAGR) of 20.8% from 2023 to 2028. The growth of the AI Chipsets   market is driven by the increasing data traffic and need for high computing power, emerging trend of autonomous vehicles, growing adoption of industrial robots, and rising focus on parallel computing in Al data centers.

Browse 183 market data Tables and 63 Figures spread through 295 Pages and in-depth TOC on "AI Chipsets Market by Hardware (Processor, Memory, Network), Technology (Machine Learning, Natural Language Processing, Computer Vision), Function (Training, Interference), End-User Industry and Region - Global Forecast to 2028"
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By hardware device, memory segment projected to grow at a high CAGR of AI Chipsets market during the forecast period.

AI-based memory is revolutionizing the way we store and access information. Traditional computer memory systems have been limited by their fixed architecture and capacity, requiring constant upgrades and replacements to keep up with expanding data needs. However, Al-based memory can dynamically adapt and learn from user behavior to optimize storage and retrieval efficiency. By utilizing machine learning algorithms, Al-based memory systems can analyze patterns in user behavior and data usage to predict future needs and adjust accordingly. This technology is particularly beneficial for large-scale data centers and cloud storage systems, where storing and accessing vast amounts of data efficiently is crucial. Additionally, Al-based memory can enhance security measures by using predictive analysis to detect and prevent potential threats. Implementing Al-based memory can greatly enhance data storage and management capabilities, leading to more efficient and secure systems.

Machine Learning in technology segment in AI Chipsets market is expected to account for second highest share during the forecast period.

Machine learning allows systems to learn deprived of being explicitly programmed. Machine learning technology can reliably and quickly scan, parse, and react to anomalies. It enables systems to improve their performance with experience automatically. It aims to advance a computer program/algorithm which can access data and can be used to train itself with no human intervention. Machine learning technology is predominantly used in AI solutions due to the availability of big data to train machine learning models and the high adoption of machine learning technology by enterprises and federal agencies to gain useful insights.

Training segment will account for highest CAGR during the forecast period.

In the context of Al, training is the process of developing an algorithm that can infer a result from data or processes. Training an Al model involves providing the learning algorithm with training data to learn from. The training data must include the correct answer, known as a target or target attribute. The learning algorithm finds patterns in the training data, maps the input data attributed to the target, and outputs an ML model that captures these patterns. Training is computationally costly and is best accelerated with GPUs. The time undertaken to go through all the training samples can be decreased using GPU compared with CPU, even when using a small dataset.

Consumer electronics segment will account for the largest market share during the forecast period.

Devices considered under smart homes include smart speakers, smart IP cameras, and domestic robots. Smart speakers are the major contributors to the AI chipset market for smart homes. The major players offering smart speakers include Amazon (US), Google (US), Apple (US), and Baidu (China). The efforts of smart speaker manufacturers to reduce latency have facilitated the growth of the AI chipset market. The increasing adoption of automation in several redundant and monotonous domestic applications such as cleaning, dusting, and cooking creates a strong demand for domestic robots. The integration of AI chipsets into domestic robots could further provide more assistance to domestic work and hence could witness fast growth during the forecast period.

Asia Pacific will account for the highest CAGR during the forecast period.

The AI chipsets market in Asia Pacific includes economies such as South Korea, Japan, China, and India. Asia Pacific includes few of the fastest growing and foremost industrialized economies, such as China, Japan, and India. The region is perceiving a dynamic change in the implementation of new technologies and innovations across industries. Growing acceptance of deep learning and NLP technologies for finance, agriculture, marketing, and law applications is also driving the market in this region. The rising eCommerce, increasing internet penetration, and online streaming have resulted in the growth of marketing industries. Marketers are now looking for more sophisticated, state-of-the-art marketing solutions for ever-growing consumer base. This has further resulted in the rising adoption of AI-enabled solutions for marketing.

Key Players

Key companies operating in the AI Chipsets  market are Intel Corporation (US), NVIDIA Corporation (US), IBM (US), AMD (US), Micron Technology Inc (US), Qualcomm Technologies, Inc (US), Samsung Electronics Co., Ltd. (South Korea), Apple Inc. (US), Alphabet Inc. (US), Huawei Technologies Co., Ltd. (China), Texas Instruments Incorporated  (US), NXP Semiconductors (Netherlands), Infineon Technologies Inc (Germany), Graphcore (UK), MediaTek Inc. (Taiwan), Analog Devices, Inc. (US), STMicroelectronics (Switzerland), among others.

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