Global Machine Learning Chip Market Overview 2023-2028
The global machine learning chip market size reached US$ 7.8 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 35.0 Billion by 2028, exhibiting a growth rate (CAGR) of 25.4% during 2023-2028.
Factors Affecting the Growth of the Machine Learning Chip Industry:
- Growing Demand for Artificial Intelligence (AI) and Machine Learning (ML) Applications:
As businesses across various industries adopt AI and ML technologies to enhance efficiency, productivity, and decision-making processes, the demand for specialized hardware accelerators, such as ML chips, is rising. AI and ML applications often involve computationally intensive workloads, especially when dealing with tasks like deep learning and neural network training. General-purpose processors may not be efficient enough for these tasks, leading to the need for specialized hardware like ML chips. AI and ML workloads demand a significant amount of computational power, and traditional processors may consume a considerable amount of energy. ML chips are often designed with energy efficiency in mind, making them more suitable for handling the specific demands of AI and ML applications.
- Rise of Neuromorphic and Quantum Computing:
Neuromorphic chips are designed to mimic the structure and functioning of the human brain. They excel in handling complex, parallel computations, making them well-suited for certain types of machine learning tasks, particularly those related to pattern recognition and sensory processing. This increased processing power can lead to faster and more efficient execution of machine learning algorithms. Besides this, quantum algorithms can potentially solve specific sorts of problems much faster than classical algorithms. As a result, ML algorithms can be optimized for quantum computers to achieve better performance on specific tasks, such as optimization problems and ML models with certain structures.
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- Favorable Government Initiatives:
Governments may allocate funds to support research and development in the field of artificial intelligence (AI) and machine learning, including the development of specialized hardware like ML chips. This financial support can accelerate innovation and the creation of more powerful and efficient ML chips. Governments can encourage innovation in the ML chip sector by providing support to startups and small businesses. This support may come in the form of grants, tax incentives, or incubator programs, fostering a more vibrant and competitive market. Initiatives aimed at enhancing education and workforce development in AI and ML can contribute to a skilled workforce.
Global Machine Learning Chip Trends and Drivers:
Innovation and product differentiation are becoming central to gaining a competitive edge. Companies are investing significantly in research and development (R&D) to introduce chips with enhanced processing capabilities, improved energy efficiency, and compatibility with a wide array of machine learning frameworks. Strategic partnerships and collaborations between chip manufacturers, software developers, and AI solution providers are also on the rise, fostering a holistic approach to addressing the evolving needs of the market. Industries ranging from healthcare and finance to manufacturing and logistics are incorporating ML algorithms to derive actionable insights from vast datasets. This cross-industry adoption is creating a robust demand for specialized chips capable of handling diverse workloads.
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Global Machine Learning Chip Market 2023-2028 Analysis and Segmentation:
Top Key Players covered in this report are:
Advanced Micro Devices Inc., Amazon Web Services Inc. (Amazon.com Inc.), Cerebras Inc., Google LLC, Graphcore, Intel Corporation, International Business Machines Corporation, NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics Co. Ltd. and Taiwan Semiconductor Manufacturing Company Limited
The report segmented the market on the basis of region, technology, chip type and industry vertical.
Machine Learning Chip Market Report Segmentation:
By Technology:
- System-on-Chip (SoC)
- System-in-Package
- Multi-chip Module
- Others
System-on-Chip (SoC) is the most prevalent method as it integrates multiple electronic components, such as processors, memory, input/output interfaces, and sometimes even analog components, onto a single chip.
By Chip Type:
- GPU
- ASIC
- FPGA
- CPU
- Others
GPU accounted for the largest market share due to its capability of delivering high graphics performance.
By Industry Vertical:
- BFSI
- IT and Telecom
- Media and Advertising
- Retail
- Healthcare
- Automotive
- Others
BFSI represented the largest segment as rely on machine learning chips to handle large volumes of data and perform parallel processing efficiently.
Regional Insights:
- North America: (United States, Canada)
- Asia Pacific: (China, Japan, India, South Korea, Australia, Indonesia, Others)
- Europe: (Germany, France, United Kingdom, Italy, Spain, Russia, Others)
- Latin America: (Brazil, Mexico, Others)
- Middle East and Africa
North America’s dominance in the machine learning chip market is attributed to the rising implementation of favorable government polices and increasing automation of business operations.
Key highlights of the report:
- Market Performance (2017-2022)
- Market Outlook (2023- 2028)
- Porter’s Five Forces Analysis
- Market Drivers and Success Factors
- SWOT Analysis
- Value Chain
- Comprehensive Mapping of the Competitive Landscape
If you need specific information that is not currently within the scope of the report, we can provide it to you as a part of the customization.
About Us:
IMARC Group is a leading market research company that offers management strategy and market research worldwide. We partner with clients in all sectors and regions to identify their highest-value opportunities, address their most critical challenges, and transform their businesses.
IMARC’s information products include major market, scientific, economic and technological developments for business leaders in pharmaceutical, industrial, and high technology organizations. Market forecasts and industry analysis for biotechnology, advanced materials, pharmaceuticals, food and beverage, travel and tourism, nanotechnology and novel processing methods are at the top of the company’s expertise.
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