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The machine learning chips market size is estimated to increase by USD 22.27 billion and grow at a CAGR of 30.91% between 2022 and 2027. Market growth hinges on various factors, notably the proliferation of online data centers housing numerous servers powered by central processing units (CPUs), alongside the utilization of artificial intelligence (AI) technology for enhancing energy efficiency, infrastructure management, server optimization, security, and diverse applications. However, challenges persist, such as the global semiconductor chip shortage, the cyclicality inherent in the semiconductor industry, and the complexities associated with comprehending data.
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This market report extensively covers market segmentation by end-user (BDSI, IT and telecom, media and advertising, and others), technology (system-on-chip (SOC), system-in-package, multi-chip module, and others), and geography (North America, Europe, APAC, South America, and Middle East and Africa). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market data from 2017 to 2021.
The market share growth by the BFSI segment will be significant during the forecast period. They have revolutionized the BFSI industry. The entire BFSI industry is driven by the customer data that financial companies have access to. AI is used by a number of marketing technologies, including Data Management Platforms (DMPs) and Customer Data Platforms (CDPs), to improve and personalize user engagements across a variety of digital channels. Cookies are used to track a user's online activity so that more relevant messages can be sent to them. Marketing has become more targeted and pertinent thanks to AI. As a result, businesses are able to increase their online revenue and engage customers across multiple touchpoints.
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The BFSI segment was valued at USD 1.53 billion in 2017 and continued to grow until 2021. The marketing landscape has been transformed completely by the emergence and use of machine learning and AI. The gap between the marketer and the customer is growing smaller steadily due to this. Marketers in the BFSI industry can improve their current and upcoming marketing campaigns by understanding their customers' past behavior better. In the insurance industry, the usage of AI can help in reducing operating costs and, at the same time, can increase customer satisfaction during the renewal of policies, claims processing, and other services. These factors are anticipated to augment the demand from the BFSI industry, thus, propelling the growth of the market during the forecast period.
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North America is estimated to contribute 46% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. The growth of the market in North America is driven by increasing investments in autonomous vehicles. These vehicles are integrated with advanced systems, such as advanced driver assistance systems (ADAS), heads-up display (HUD), light detection and ranging (LiDAR), and radio detection and ranging (RADAR). Electronic components such as sensors, microcontrollers, microprocessors, and other radio frequency (RF) components generate and process a large amount of data in real time.
Several automotive OEMs are working toward commercializing autonomous vehicles, which is providing ample opportunities for machine learning chip manufacturers to tap into the untapped potential of the market. The integration of advanced human-machine interface (HMI) technologies, along with developments in wired and wireless communication technologies for automotive applications, is expected to have a positive impact on the growth of the market in North America during the forecast period.
The Machine Learning Chips Market is experiencing remarkable growth driven by various factors. These include the integration of Artificial Intelligence (AI) and deep learning algorithms, facilitating applications like cybersecurity and fraud detection systems. This growth is further propelled by advancements in System-on-Chip (SoC) and multi-chip module technologies. Additionally, the market benefits from the increasing demand for big data analytics and cloud computing solutions. Integration with the Internet of Things (IoT) and vertical-specific solutions enhance its utility across diverse sectors. However, challenges persist due to cybersecurity threats and the global chip shortage. Yet, innovations like Explainable AI (XAI) and federated learning promise to address these concerns, ensuring continued market expansion. Our researchers analyzed the data with 2022 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
The global market is experiencing robust growth driven by the adoption of machine learning chips in autonomous vehicles. Automotive companies recognize the pivotal role of these chips in achieving high levels of vehicle automation, fueling increased demand in this sector. With sensors, cameras, radar, LIDAR, and ultrasonic instruments generating vast amounts of data, these processors analyze the information to make split-second decisions on the road. Machine learning chips enable advanced features like ADAS, intuitive user interfaces, and automotive cloud services, offering advantages such as object recognition, reduced power consumption, and improved perception. This trend presents lucrative opportunities for vendors to expand their market presence and revenue streams.
Increasing investments in AI start-ups is the primary trend shaping the global market. AI technology is still in the development phase, and hence, its implementation is growing rapidly across many industries. Several companies, such as start-ups, are entering the market to capitalize on the growing demand for AI technology. Due to the huge growth potential of the global market, several start-ups have been receiving significant investments from venture capitalists and major chip manufacturers for the development of AI platforms and chipsets.
For instance, in May 2021, Shanghai-based start-up Innostar Semiconductor raised USD 100 million funding in a pre-series A round funding, which was led by Shanghai Lianhe Investment and joined by New Alliance as well as new investors Atlas Capital and KQ Capital. The company will use the funding for the development of storage and resistive RAM chips. In May 2020, Tessolve received funding of USD 40.0 million as a private equity investment from Novo Tellus Capital Partners. The company will use this funding to expand its chip and ASIC design business and embedded service offerings. These factors will drive the growth of the market in focus during the forecast period.
The cyclical nature of the semiconductor industry is a major challenge impeding the growth of the global market. The fluctuations in demand for electronic products, such as consumer electronic devices and mobile devices, make forecasting in the global market extremely difficult. These fluctuations can also lead to the oversupply or undersupply of semiconductor ICs. In the case of oversupply, machine learning chip manufacturers can fulfill the demand for semiconductor ICs without expanding their manufacturing capacity, which reduces their capital spending. In the case of undersupply, the demand will be hard to fulfill due to the lengthy manufacturing process.
Thus, vendors might manufacture based on forecasts of customer demand, which may fluctuate significantly. Such fluctuations may lead to high inventory and manufacturing costs before actual sales take place. Hence, vendors would require high amounts of working capital to meet these costs. Also, inaccurate forecasts or cancellations/delays in orders for machine learning and other types of chips can adversely affect the operations of vendors, which leads to a huge loss for vendors in the market. Such factors may hinder market growth during the forecast period.
The market report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Global Market Customer Landscape
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Advanced Micro Devices Inc.- The company offers machine learning chips such as AMD Instinct. This segment focuses on offering CPUs, APUs, and chipsets for desktop and notebook personal computers.
The research report also includes detailed analyses of the competitive landscape of the market and information about 20 market players, including:
Qualitative and quantitative analysis of vendors has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.
The market report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027.
The market is experiencing exponential growth, fueled by the surge in demand for deep learning algorithms and the need for efficient cybersecurity and fraud detection systems. With advancements in big data analytics and cloud computing, the industry is witnessing a revolution in hardware infrastructure, including ML chips and intellectual property cores. Various sectors like automotive, healthcare, media, IT, telecommunications, and BFSI are adopting ML chips for digitalization and innovation. Moreover, the integration of AI with IoT, edge computing, and explainable AI (XAI) is shaping vertical-specific solutions to combat cybersecurity threats and enhance network infrastructures, ushering in a new era of AI-driven technologies.
The market is experiencing rapid growth driven by advancements in technology across various industries such as automotive, healthcare, media, IT, telecommunications, BFSI, smart cities, and smart homes. As cyber-attacks become more sophisticated, the need for efficient cybersecurity measures is heightened. Machine learning (ML) chips play a crucial role in powering deep learning-based applications and enhancing cybersecurity with innovations like explainable AI (XAI) integration and federated learning. Silicon Labs and other key players are innovating in advanced system-on-chips (SoCs) and neural processing units (NPU) to meet the growing demand for GPUs and AI/ML chips.
Moreover, the market is witnessing significant growth, driven by advancements in design and tool flows, alongside innovations in transistors, particularly within sectors like automotive, healthcare, media, advertising, IT, and telecommunications. Moreover, the BFSI industry is embracing machine learning chips for enhanced data processing and security. With the integration of AI into IoT devices, coupled with big data technologies, machine learning chips are revolutionizing computer information systems and networks. Personal devices are also benefiting from innovations in advanced SoCs, GPUs, CUs, ALUs, AGUs, and MMUs, catering to diverse applications like quantum computing, robotics, NLP, and more.
Data Bridge Market Research is a leading provider of market intelligence and consulting services, catering to various industries including the automotive, healthcare, media and advertising, information technology (IT), telecommunication, and banking, financial services, and insurance (BFSI) sectors. With a focus on delivering comprehensive insights and analysis, Data Bridge Market Research assists organizations in making informed decisions and staying competitive in dynamic markets. In the automotive industry, Data Bridge Market Research offers in-depth analysis of market trends, technological advancements, and competitive landscape to help companies strategize and capitalize on emerging opportunities. Similarly, within the healthcare industry, their research services cover a wide range of topics including pharmaceuticals, medical devices, healthcare IT, and digital health solutions. For the media and advertising industry, Data Bridge Market Research provides insights into consumer behavior, advertising trends, and digital media strategies. Their expertise in information technology (IT) encompasses research on software, hardware, cloud computing, cybersecurity, and emerging technologies such as artificial intelligence (AI) and natural language processing (NLP).
In the telecommunication sector, Information technology (IT) industry, and Telecommunication industry, Data Bridge Market Research offers valuable insights into market dynamics, regulatory environment, and technological innovations shaping the industry landscape. Similarly, their research services cater to the banking, financial services, and insurance (BFSI) industry, covering topics such as fintech, digital banking, insurance technology (insurtech), and risk management. With a focus on emerging technologies, Data Bridge Market Research provides analysis and forecasts on topics such as natural language processing (NLP), AI integration with the internet of things (IoT), and innovation in advanced system-on-chips (SoCs). These insights enable organizations to stay ahead of the curve and harness the full potential of these transformative technologies. Overall, Data Bridge Market Research serves as a trusted partner for businesses across various industries, offering actionable insights, strategic recommendations, and customized solutions to support their growth and success in today's competitive landscape.
Machine Learning Chips Market Scope |
|
Report Coverage |
Details |
Page number |
182 |
Base year |
2022 |
Historic period |
2017-2021 |
Forecast period |
2023-2027 |
Growth momentum & CAGR |
Accelerate at a CAGR of 30.91% |
Market growth 2023-2027 |
USD 22.28 billion |
Market structure |
Fragmented |
YoY growth 2022-2023(%) |
24.49 |
Regional analysis |
North America, Europe, APAC, South America, and Middle East and Africa |
Performing market contribution |
North America at 46% |
Key countries |
US, China, Taiwan, UK, and Germany |
Competitive landscape |
Leading Vendors, Market Positioning of Vendors, Competitive Strategies, and Industry Risks |
Key companies profiled |
Advanced Micro Devices Inc., Alphabet Inc., Baidu Inc., Broadcom Inc., Cerebras Systems Inc., Fujitsu Ltd., Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd., and Tesla Inc. |
Market dynamics |
Parent market analysis, Market forecasting, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for forecast period. |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
We can help! Our analysts can customize this market research report to meet your requirements.
1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by End-user
7 Market Segmentation by Technology
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Trends
11 Vendor Landscape
12 Vendor Analysis
13 Appendix
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