Artificial Intelligence Chipsets Sales

Artificial Intelligence Chipsets Sales Market Outlook

The global artificial intelligence chipsets market is projected to reach approximately USD 118 billion by 2035, with a compound annual growth rate (CAGR) of around 30% from 2025 to 2035. The rapid proliferation of AI technologies and the increasing integration of AI into various sectors such as automotive, healthcare, and consumer electronics are key factors driving the growth of this market. Moreover, the demand for high-performance computing for data-intensive applications is significantly increasing, leading to the adoption of advanced chipsets tailored for AI workloads. As organizations endeavor to harness the power of machine learning and deep learning, the need for specialized AI chipsets becomes prominent, thus further fueling market expansion. The ongoing research and development activities directed toward enhancing AI efficiency, performance, and power consumption are anticipated to contribute significantly to the market's growth trajectory.

Growth Factor of the Market

One of the primary growth factors propelling the artificial intelligence chipsets market is the increasing demand for high-performance computing solutions across diverse industries. As businesses strive to leverage big data analytics and machine learning, the necessity for chipsets that can process vast amounts of data in real-time has become more critical. Additionally, the rising adoption of AI technologies in consumer electronics, such as smartphones and smart home devices, is creating a surge in demand for efficient and powerful AI chipsets. The automotive industry is also a significant contributor, with the growing trend of autonomous vehicles requiring advanced processing capabilities for AI algorithms. Furthermore, government initiatives promoting AI research and development are fostering innovation and investment in AI chipset technologies, thereby enhancing market growth. Lastly, the shift towards cloud-based AI services is influencing organizations to invest in robust chipset solutions that can support cloud computing and storage needs.

Key Highlights of the Market

• The global artificial intelligence chipsets market is anticipated to witness significant growth with a CAGR of around 30% from 2025 to 2035.
• The increasing demand for AI applications in automotive, healthcare, and consumer electronics is driving market expansion.
• High-performance computing and real-time data processing capabilities are crucial factors influencing chipset adoption.
• Government initiatives and investments in AI technology are fostering innovation within the chipset sector.
• The shift towards cloud-based AI solutions is prompting organizations to invest in advanced AI chipset technologies.

By Product Type

GPU:

Graphics Processing Units (GPUs) are one of the most widely used chipsets in the field of artificial intelligence. Their parallel processing capability allows them to handle multiple operations simultaneously, making them ideal for training complex neural networks. This capability is particularly beneficial in applications such as image and speech recognition, where vast amounts of data must be processed quickly and efficiently. The increasing demand for GPUs in sectors like gaming, automotive, and healthcare is driving market growth, as these industries require advanced graphical computations and AI-based functionalities. Furthermore, continuous advancements in GPU technology, including the development of more powerful models with enhanced energy efficiency, are expected to further bolster their adoption for AI applications.

FPGA:

Field Programmable Gate Arrays (FPGAs) offer a unique advantage in the artificial intelligence chipsets market due to their reconfigurable nature. Unlike fixed-function chips, FPGAs can be tailored to specific tasks, allowing for optimization based on the application's needs. This flexibility is particularly valuable in sectors such as telecommunications and aerospace, where requirements may evolve over time. Additionally, FPGAs provide high processing speeds and low latency, which are crucial for real-time AI applications. Their ability to efficiently handle parallel processing tasks makes them suitable for machine learning and data analysis applications, solidifying their position in the AI chipset market. The growing trend towards customized hardware solutions is likely to enhance the demand for FPGAs in AI applications.

ASIC:

Application-Specific Integrated Circuits (ASICs) are designed for a singular purpose, making them highly efficient for specific workloads in artificial intelligence. ASICs are particularly advantageous in environments where energy efficiency and processing speed are paramount, such as data centers and edge computing devices. Their specialized nature allows for the optimization of AI tasks, enabling significant improvements in performance compared to general-purpose processors. As AI workloads continue to grow in complexity, the demand for ASICs is expected to increase, especially in areas like cryptocurrency mining and large-scale machine learning tasks. The development of industry-specific ASICs will likely drive further adoption in sectors requiring dedicated AI solutions.

CPU:

Central Processing Units (CPUs) remain a fundamental component in the artificial intelligence chipsets market, as they are essential for general-purpose computing tasks. While GPUs and specialized chipsets are preferred for heavy AI workloads, CPUs are integral for handling various tasks, including data preprocessing and integration with other systems. The continuous evolution of CPUs, with enhancements in multi-core architectures and hyper-threading capabilities, is enabling them to better support AI applications. Additionally, the integration of AI capabilities within CPU designs is creating opportunities for improved processing efficiency. The flexibility of CPUs in executing diverse functions makes them indispensable in the overall AI ecosystem.

Neural Network Processor:

Neural Network Processors (NNPs) are specifically designed to accelerate neural network computations, making them highly effective for artificial intelligence applications. NNPs are optimized for tasks such as deep learning, where they can perform matrix multiplications and convolutions at remarkable speeds. This specialization allows for enhanced performance in applications like image recognition, natural language processing, and autonomous driving. As the demand for AI-driven solutions continues to rise, the adoption of NNPs is expected to increase significantly. Leading technology companies are investing in developing advanced NNP architectures to further enhance processing capabilities, which is likely to create a robust market for these specialized chipsets.

By Application

Smartphones:

The integration of artificial intelligence in smartphones has transformed user experience and functionality. AI chipsets enable features such as facial recognition, voice assistants, and camera enhancements, making smartphones more intuitive and efficient. These chipsets help optimize performance, manage battery consumption, and enhance security, driving consumer demand for advanced AI capabilities. As smartphone manufacturers strive to differentiate their products in a competitive market, investment in AI chipsets is likely to increase. The growing trend of AI-driven applications and services in mobile devices is anticipated to further propel market growth in this segment.

Automotive:

The automotive industry is rapidly adopting artificial intelligence technologies, particularly in the development of autonomous vehicles. AI chipsets play a crucial role in processing real-time data from sensors, cameras, and radar systems to facilitate safe navigation and decision-making. These chipsets support applications such as advanced driver-assistance systems (ADAS), predictive maintenance, and infotainment systems. As regulatory bodies and consumers demand safer and more efficient vehicles, the integration of AI chipsets in automotive applications is expected to grow significantly. The increasing investment in autonomous driving technology by major automotive manufacturers further underscores the importance of AI chipsets in this sector.

Healthcare:

In the healthcare sector, artificial intelligence chipsets are driving innovations in diagnostics, treatment personalization, and operational efficiency. These chipsets enable the analysis of vast amounts of medical data, facilitating early disease detection and the development of tailored treatment plans. Applications such as medical imaging, drug discovery, and patient monitoring benefit from AI processing capabilities, leading to improved patient outcomes. As healthcare institutions adopt AI technologies for better diagnosis and treatment, the demand for specialized chipsets designed for healthcare applications is projected to rise significantly. The growing emphasis on telemedicine and remote monitoring solutions further amplifies the need for efficient AI chipsets in the healthcare landscape.

Robotics:

The robotics industry is increasingly leveraging artificial intelligence chipsets to enhance the capabilities of robotic systems. AI chipsets enable robots to process information from their environment, make autonomous decisions, and learn from interactions. Applications range from industrial automation to service robots in hospitality and healthcare. The ability of robots to adapt to changing conditions and execute complex tasks relies heavily on efficient AI processing power. As industries seek to automate operations and improve efficiency, the demand for AI chipsets in robotics is expected to grow. The ongoing advancements in robotics technology, including the use of machine learning and computer vision, will drive further adoption of specialized chipsets in this field.

IoT:

The Internet of Things (IoT) is rapidly evolving, with artificial intelligence playing a pivotal role in enhancing device capabilities. AI chipsets enable IoT devices to process data locally, reducing latency and improving real-time decision-making. Applications in smart home automation, industrial IoT, and connected health devices benefit from the integration of AI technologies. As the number of connected devices continues to rise, the demand for efficient and power-effective AI chipsets tailored for IoT applications is projected to increase significantly. The synergy between AI and IoT technologies is expected to lead to innovative solutions that enhance user experience and operational efficiency across various sectors.

By Distribution Channel

Online Sales:

Online sales have become a crucial distribution channel for artificial intelligence chipsets, driven by the convenience and accessibility they offer to consumers and businesses alike. E-commerce platforms and specialized electronics websites enable customers to compare products and prices, leading to informed purchasing decisions. The growing trend of direct-to-consumer sales by manufacturers further enhances the online retail landscape. Additionally, the ability to provide extensive product information, specifications, and customer reviews fosters a transparent buying environment that caters to diverse customer needs. As more consumers turn to online shopping for electronics, the online sales channel for AI chipsets is expected to experience significant growth, supported by promotional activities and competitive pricing strategies.

Offline Sales:

Despite the growing prominence of online sales, offline sales remain a vital distribution channel for artificial intelligence chipsets, particularly in the B2B space. Physical retail locations, including electronics stores and specialty outlets, allow customers to engage directly with sales personnel, facilitating personalized consultations and product demonstrations. This hands-on experience can be crucial for businesses looking to invest in AI chipsets, as they can assess performance and compatibility with existing systems. Furthermore, strategic partnerships between manufacturers and distributors ensure that AI chipsets are readily available in retail environments, catering to immediate demand. As businesses and consumers continue to explore AI technologies, the offline sales channel will continue to play a significant role in the overall distribution strategy.

By Technology

Machine Learning:

Machine learning is a critical technology driving the artificial intelligence chipsets market. Chipsets designed for machine learning applications are optimized to perform complex calculations and data analyses quickly. These chipsets enhance capabilities in various fields, including predictive analytics, natural language processing, and image recognition. As organizations increasingly leverage machine learning for data-driven decision-making, the demand for specialized chipsets that can efficiently support these applications is expected to rise. Continuous advancements in machine learning algorithms, coupled with growing investments in AI research, will likely propel the development and adoption of machine learning-focused chipsets.

Natural Language Processing:

Natural Language Processing (NLP) is another essential technology that is influencing the design and development of artificial intelligence chipsets. NLP chipsets are tailored to process and analyze human language, enabling applications such as virtual assistants, chatbots, and sentiment analysis tools. The increasing use of voice-activated systems across industries has driven the demand for chipsets that can efficiently handle NLP tasks. As advancements in NLP algorithms continue to evolve, the need for high-performance AI chipsets capable of supporting these technologies will grow significantly. Companies are investing in creating chipsets that enhance NLP performance, thereby expanding their applications across multiple sectors.

Computer Vision:

Computer vision technology plays a pivotal role in enabling machines to interpret and understand visual information, making it a crucial area for artificial intelligence chipsets. Chipsets optimized for computer vision applications are designed to process and analyze images and videos in real time, facilitating functionalities such as facial recognition, object detection, and autonomous navigation. With the increasing integration of AI in sectors such as security, retail, and automotive, the demand for specialized chipsets that can efficiently handle computer vision tasks is on the rise. Continuous advancements in imaging technologies and algorithms are expected to drive innovation and growth within the computer vision segment of the AI chipsets market.

Robotics:

Artificial intelligence chipsets tailored for robotics applications are essential for enhancing the capabilities of robotic systems. These chipsets enable robots to process sensory data, make autonomous decisions, and learn from experiences, significantly improving their functionality. As industries seek to automate processes and improve efficiency, the demand for AI chipsets in robotics is expected to grow. Advances in robotics technology, combined with increased investments in automation solutions, are likely to drive the adoption of specialized chipsets. The ongoing development of machine learning and computer vision technologies will further enhance the capabilities of AI chipsets in the robotics sector.

Autonomous Vehicles:

Artificial intelligence chipsets play a critical role in the development of autonomous vehicles, providing the necessary processing power to analyze vast amounts of data from sensors and cameras. These chipsets enable real-time decision-making and safe navigation, ensuring that autonomous vehicles can operate effectively in complex environments. As the automotive industry continues to innovate and advance towards fully autonomous driving, the demand for specialized AI chipsets designed specifically for these applications is expected to rise significantly. Ongoing research and development efforts focused on enhancing the performance and reliability of AI chipsets for autonomous vehicles will further drive market growth in this segment.

By Region

The artificial intelligence chipsets market exhibits significant regional variations in demand and growth potential. North America holds a prominent share of the global market, driven by strong investments in AI research and development, as well as the presence of major technology companies and startups in the region. The region is expected to maintain a CAGR of approximately 28% during the forecast period, as companies continue to innovate and release new AI-driven products and services. The demand for AI chipsets in sectors such as automotive, healthcare, and consumer electronics is particularly robust in North America, contributing to its leadership position in the market.

In Europe, the artificial intelligence chipsets market is experiencing rapid growth, fueled by increasing government initiatives and funding for AI projects across various industries. The region is witnessing a rising demand for AI technologies in sectors such as manufacturing, automotive, and healthcare, which is driving the adoption of specialized chipsets. Furthermore, the growing focus on smart manufacturing and Industry 4.0 initiatives is contributing to the demand for AI chipsets in Europe. The Asia Pacific region is also emerging as a significant growth area, with countries like China and Japan investing heavily in AI research and implementation, leading to increased demand for AI chipsets. The combined growth in these regions is expected to propel the overall market towards its projected size.

Opportunities

The artificial intelligence chipsets market presents a plethora of opportunities across various sectors. One of the most notable opportunities lies in the continuous advancement of AI technology, which is fostering the development of new and innovative chipset solutions. As industries such as automotive, healthcare, and consumer electronics increasingly integrate AI functionalities, the demand for specialized chipsets that can optimize performance will continue to rise. Companies that invest in research and development to create cutting-edge AI chipsets with enhanced processing capabilities are well-positioned to capture a larger market share. Additionally, the growing trend of cloud computing and edge AI is creating opportunities for chipset manufacturers to provide solutions that cater to both centralized and decentralized environments, thus broadening their market reach and appeal.

Moreover, the increasing focus on sustainability and energy-efficient technologies presents further opportunities within the AI chipsets market. As governments and organizations seek to reduce their carbon footprints, the demand for chipsets that minimize energy consumption while delivering high performance is expected to rise. Manufacturers that prioritize sustainable production practices and develop environmentally friendly AI chipsets can attract environmentally conscious consumers and businesses. Additionally, the expansion of AI applications in emerging markets, such as smart cities and IoT solutions, offers significant growth potential for chipset manufacturers. By capitalizing on these emerging trends and opportunities, companies in the artificial intelligence chipsets market can enhance their competitive positioning and drive long-term growth.

Threats

Despite the promising growth potential of the artificial intelligence chipsets market, several threats could hinder market expansion. One of the most significant threats is the rapid pace of technological advancements, which can quickly render existing chipsets obsolete. Companies must continuously invest in research and development to keep up with emerging technologies and consumer demands. Failing to do so may result in decreased market share and competitiveness. Furthermore, the increasing complexity of AI applications requires chipsets to support advanced functionalities, which can be a challenge for manufacturers that lack the necessary resources and expertise. As new players enter the market with innovative solutions, established companies may face competitive pressures that could disrupt their operations and profitability.

Additionally, the artificial intelligence chipsets market is susceptible to regulatory challenges, particularly concerning data privacy and security. As AI technologies become more integrated into various applications, governments and regulatory bodies may impose stringent regulations to protect consumer data. Compliance with these regulations may require significant investments and adjustments to chipset designs, which could impact manufacturers' ability to innovate and compete effectively. Furthermore, the geopolitical landscape and trade tensions between countries can affect supply chains and access to critical components, posing additional challenges for chipset manufacturers. Addressing these threats will be crucial for ensuring sustained growth and success in the AI chipsets market.

Competitor Outlook

• Intel Corporation
• NVIDIA Corporation
• Advanced Micro Devices (AMD)
• Qualcomm Technologies, Inc.
• Google LLC
• IBM Corporation
• Texas Instruments Incorporated
• Micron Technology, Inc.
• Graphcore Limited
• Samsung Electronics
• Xilinx, Inc.
• Broadcom Inc.
• Marvell Technology Group Ltd.
• MediaTek Inc.
• Analog Devices, Inc.

The competitive landscape of the artificial intelligence chipsets market is characterized by a mix of established technology giants and emerging startups, all vying for a share of the growing demand for AI solutions. Major players such as Intel Corporation and NVIDIA Corporation dominate the market with their extensive portfolios of AI chipsets, which are widely used across various applications. These companies invest heavily in research and development, continuously enhancing their product offerings to stay ahead of the competition. Furthermore, collaborations and partnerships between these companies and other technology firms are common, aimed at integrating AI capabilities into their existing products and services.

Other significant competitors, such as AMD and Qualcomm Technologies, are also making strides in the AI chipsets market by focusing on specialized products tailored to specific applications. For instance, Qualcomm has been advancing its AI capabilities in mobile devices, while AMD is leveraging its GPU technology to cater to AI workloads in gaming and data centers. Additionally, emerging companies like Graphcore and Google are gaining traction by offering innovative solutions that leverage advanced AI architectures and machine learning capabilities. The competition in this sector is expected to intensify as the demand for AI technologies continues to grow, prompting companies to innovate and adapt to changing market dynamics.

In conclusion, the artificial intelligence chipsets market is poised for significant growth, driven by advancements in AI technology, increasing adoption across various industries, and the ongoing push for high-performance computing solutions. Key players in the market are continuously striving to enhance their chipsets’ capabilities, address emerging challenges, and capitalize on new opportunities. As the landscape evolves, companies that focus on innovation, sustainability, and customer-centric solutions will be well-positioned to thrive in this rapidly growing market.

• 1 Appendix

  • 1.1 List of Tables
  • 1.2 List of Figures

• 2 Introduction

  • 2.1 Market Definition
  • 2.2 Scope of the Report
  • 2.3 Study Assumptions
  • 2.4 Base Currency & Forecast Periods

• 3 Market Dynamics

  • 3.1 Market Growth Factors
  • 3.2 Economic & Global Events
  • 3.3 Innovation Trends
  • 3.4 Supply Chain Analysis

• 4 Consumer Behavior

  • 4.1 Market Trends
  • 4.2 Pricing Analysis
  • 4.3 Buyer Insights

• 5 Key Player Profiles

  • 5.1 Google LLC
    • 5.1.1 Business Overview
    • 5.1.2 Products & Services
    • 5.1.3 Financials
    • 5.1.4 Recent Developments
    • 5.1.5 SWOT Analysis
  • 5.2 Xilinx, Inc.
    • 5.2.1 Business Overview
    • 5.2.2 Products & Services
    • 5.2.3 Financials
    • 5.2.4 Recent Developments
    • 5.2.5 SWOT Analysis
  • 5.3 Broadcom Inc.
    • 5.3.1 Business Overview
    • 5.3.2 Products & Services
    • 5.3.3 Financials
    • 5.3.4 Recent Developments
    • 5.3.5 SWOT Analysis
  • 5.4 MediaTek Inc.
    • 5.4.1 Business Overview
    • 5.4.2 Products & Services
    • 5.4.3 Financials
    • 5.4.4 Recent Developments
    • 5.4.5 SWOT Analysis
  • 5.5 IBM Corporation
    • 5.5.1 Business Overview
    • 5.5.2 Products & Services
    • 5.5.3 Financials
    • 5.5.4 Recent Developments
    • 5.5.5 SWOT Analysis
  • 5.6 Graphcore Limited
    • 5.6.1 Business Overview
    • 5.6.2 Products & Services
    • 5.6.3 Financials
    • 5.6.4 Recent Developments
    • 5.6.5 SWOT Analysis
  • 5.7 Intel Corporation
    • 5.7.1 Business Overview
    • 5.7.2 Products & Services
    • 5.7.3 Financials
    • 5.7.4 Recent Developments
    • 5.7.5 SWOT Analysis
  • 5.8 NVIDIA Corporation
    • 5.8.1 Business Overview
    • 5.8.2 Products & Services
    • 5.8.3 Financials
    • 5.8.4 Recent Developments
    • 5.8.5 SWOT Analysis
  • 5.9 Samsung Electronics
    • 5.9.1 Business Overview
    • 5.9.2 Products & Services
    • 5.9.3 Financials
    • 5.9.4 Recent Developments
    • 5.9.5 SWOT Analysis
  • 5.10 Analog Devices, Inc.
    • 5.10.1 Business Overview
    • 5.10.2 Products & Services
    • 5.10.3 Financials
    • 5.10.4 Recent Developments
    • 5.10.5 SWOT Analysis
  • 5.11 Micron Technology, Inc.
    • 5.11.1 Business Overview
    • 5.11.2 Products & Services
    • 5.11.3 Financials
    • 5.11.4 Recent Developments
    • 5.11.5 SWOT Analysis
  • 5.12 Qualcomm Technologies, Inc.
    • 5.12.1 Business Overview
    • 5.12.2 Products & Services
    • 5.12.3 Financials
    • 5.12.4 Recent Developments
    • 5.12.5 SWOT Analysis
  • 5.13 Advanced Micro Devices (AMD)
    • 5.13.1 Business Overview
    • 5.13.2 Products & Services
    • 5.13.3 Financials
    • 5.13.4 Recent Developments
    • 5.13.5 SWOT Analysis
  • 5.14 Marvell Technology Group Ltd.
    • 5.14.1 Business Overview
    • 5.14.2 Products & Services
    • 5.14.3 Financials
    • 5.14.4 Recent Developments
    • 5.14.5 SWOT Analysis
  • 5.15 Texas Instruments Incorporated
    • 5.15.1 Business Overview
    • 5.15.2 Products & Services
    • 5.15.3 Financials
    • 5.15.4 Recent Developments
    • 5.15.5 SWOT Analysis

• 6 Market Segmentation

  • 6.1 Artificial Intelligence Chipsets Sales Market, By Technology
    • 6.1.1 Machine Learning
    • 6.1.2 Natural Language Processing
    • 6.1.3 Computer Vision
    • 6.1.4 Robotics
    • 6.1.5 Autonomous Vehicles
  • 6.2 Artificial Intelligence Chipsets Sales Market, By Application
    • 6.2.1 Smartphones
    • 6.2.2 Automotive
    • 6.2.3 Healthcare
    • 6.2.4 Robotics
    • 6.2.5 IoT
  • 6.3 Artificial Intelligence Chipsets Sales Market, By Distribution Channel
    • 6.3.1 Online Sales
    • 6.3.2 Offline Sales

• 7 Competitive Analysis

  • 7.1 Key Player Comparison
  • 7.2 Market Share Analysis
  • 7.3 Investment Trends
  • 7.4 SWOT Analysis

• 8 Research Methodology

  • 8.1 Analysis Design
  • 8.2 Research Phases
  • 8.3 Study Timeline

• 9 Future Market Outlook

  • 9.1 Growth Forecast
  • 9.2 Market Evolution

• 10 Geographical Overview

  • 10.1 Europe - Market Analysis
    • 10.1.1 By Country
      • 10.1.1.1 UK
      • 10.1.1.2 France
      • 10.1.1.3 Germany
      • 10.1.1.4 Spain
      • 10.1.1.5 Italy
  • 10.2 Asia Pacific - Market Analysis
    • 10.2.1 By Country
      • 10.2.1.1 India
      • 10.2.1.2 China
      • 10.2.1.3 Japan
      • 10.2.1.4 South Korea
  • 10.3 Latin America - Market Analysis
    • 10.3.1 By Country
      • 10.3.1.1 Brazil
      • 10.3.1.2 Argentina
      • 10.3.1.3 Mexico
  • 10.4 North America - Market Analysis
    • 10.4.1 By Country
      • 10.4.1.1 USA
      • 10.4.1.2 Canada
  • 10.5 Middle East & Africa - Market Analysis
    • 10.5.1 By Country
      • 10.5.1.1 Middle East
      • 10.5.1.2 Africa
  • 10.6 Artificial Intelligence Chipsets Sales Market by Region

• 11 Global Economic Factors

  • 11.1 Inflation Impact
  • 11.2 Trade Policies

• 12 Technology & Innovation

  • 12.1 Emerging Technologies
  • 12.2 AI & Digital Trends
  • 12.3 Patent Research

• 13 Investment & Market Growth

  • 13.1 Funding Trends
  • 13.2 Future Market Projections

• 14 Market Overview & Key Insights

  • 14.1 Executive Summary
  • 14.2 Key Trends
  • 14.3 Market Challenges
  • 14.4 Regulatory Landscape

Segments Analyzed in the Report

The global Artificial Intelligence Chipsets Sales market is categorized based on

By Application

• Smartphones
• Automotive
• Healthcare
• Robotics
• IoT

By Distribution Channel

• Online Sales
• Offline Sales

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision
• Robotics
• Autonomous Vehicles

By Region

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Key Players

• Intel Corporation
• NVIDIA Corporation
• Advanced Micro Devices (AMD)
• Qualcomm Technologies, Inc.
• Google LLC
• IBM Corporation
• Texas Instruments Incorporated
• Micron Technology, Inc.
• Graphcore Limited
• Samsung Electronics
• Xilinx, Inc.
• Broadcom Inc.
• Marvell Technology Group Ltd.
• MediaTek Inc.
• Analog Devices, Inc.