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市场调查报告书
商品编码
1680469

AI视觉晶片市场报告：趋势、预测与竞争分析（至2031年）

AI Vision Chip Market Report: Trends, Forecast and Competitive Analysis to 2031
出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3个工作天内

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简介目录

全球AI视觉晶片市场前景广阔，在安防、汽车、家电、物联网、无人机、机器人等市场都存在发展机会。预计全球人工智慧视觉晶片市场从 2025 年到 2031 年的复合年增长率将达到 32.4%。该市场的主要驱动力是边缘运算的日益普及以及电脑视觉技术在製造业、医疗保健、安全和自动驾驶汽车等各个行业中的日益普及。

  • Lucintel 预测，按类型划分，12nm 将在预测期内达到最高成长。
  • 从应用角度来看，安全和监控预计将实现最高成长。
  • 根据地区来看，预计亚太地区将在预测期内实现最高成长。

AI视觉晶片市场的策略性成长机会

AI视觉晶片市场受技术进步和市场需求驱动，在各个应用领域呈现出若干策略成长机会。

  • 智慧安防系统：智慧安防系统的成长为AI视觉晶片提供了巨大的机会。这些晶片透过脸部辨识、运动侦测和异常侦测等功能增强了监视录影机和安全解决方案。住宅、商业和公共部门对先进安全解决方案的需求正在推动这一应用领域的成长。
  • 自动驾驶汽车：自动驾驶汽车是人工智慧视觉晶片的主要成长领域。这些晶片对于处理导航、障碍物侦测和驾驶辅助系统中使用的视觉资料至关重要。自动驾驶技术的不断发展和汽车安全功能的进步为汽车行业的人工智慧视觉晶片创造了机会。
  • 工业自动化：人工智慧视觉晶片越来越多地用于工业自动化，例如品管、预测性维护和机器人等应用。这些晶片提高了製造过程的精度和效率，推动了智慧工厂和自动化生产线的发展。对工业 4.0 和自动化的关注正在扩大这一细分市场。
  • 医疗保健和医学影像：在医疗保健领域，人工智慧视觉晶片在医学影像处理和诊断方面存在机会。这些晶片增强了影像处理系统的功能，例如提高影像品质、即时分析和模式识别。对先进诊断工具和远端医疗日益增长的需求正在推动这一应用领域的应用。
  • 扩增实境(AR) 和虚拟实境 (VR)：AI 视觉晶片对于 AR 和 VR 应用至关重要，可提供沉浸式体验和即时互动所需的处理能力。新兴国家AR、VR技术市场的发展，为AI视觉晶片创造机会，支援游戏、训练、娱乐等应用，提升使用者体验，扩大市场潜力。

这些策略成长机会凸显了人工智慧视觉晶片的多样化应用和潜力。专注于智慧安全系统、自动驾驶汽车、工业自动化、医疗和AR/VR将使公司能够接触不断扩大的市场并满足新的需求，从而推动AI视觉晶片领域的创新和成长。

AI视觉晶片市场驱动因素与挑战

AI视觉晶片市场受到各种驱动因素​​和挑战的影响，包括技术进步、经济因素和监管考虑。

AI视觉晶片市场受以下因素驱动：

  • 技术进步：人工智慧和视觉技术的快速进步正在推动人工智慧视觉晶片市场的发展。晶片设计、处理能力和人工智慧演算法的创新正在增强视觉系统的功能，从而实现更先进、更有效率的应用。这些进步正在支援多个行业的人工智慧视觉晶片的发展。
  • 自动化需求不断增长：製造业、汽车业和安全业等行业对自动化的需求不断增长，推动了人工智慧视觉晶片的采用。这些晶片实现了先进的视觉识别和处理，支援自动化工作并提高效率。对智慧工厂、自动驾驶汽车和智慧安全系统的关注正在推动市场成长。
  • 家用电子电器的扩张：AI视觉晶片与智慧型手机、智慧家居设备等家用电子电器的整合正在推动市场扩张。消费性产品对增强影像处理和智慧功能的需求正在为AI视觉晶片製造商创造机会。这一趋势反映了先进视觉技术在日常设备中日益增长的重要性。
  • 智慧城市和基础设施的成长：智慧城市和基础设施的发展正在创造对用于监控、交通管理和公共等应用的人工智慧视觉晶片的需求。对创建智慧互联城市环境的关注正在推动视觉晶片的应用来支持这些努力，从而促进市场成长。
  • 边缘运算的进步：边缘运算的兴起正在推动对具有本地处理能力的人工智慧视觉晶片的需求。边缘AI晶片可实现即时资料分析和回应，支援自动驾驶汽车、工业自动化和智慧型装置中的应用。这一趋势反映了对高效、低延迟运算解决方案日益增长的需求。

AI视觉晶片市场面临的挑战有：

  • 开发成本高：AI视觉晶片的开发和生产涉及研究、设计和製造相关的高成本。这些成本为新参与企业设定了进入壁垒，并影响了最终用户对晶片的承受能力。管理开发成本并保持有竞争力的价格是该行业面临的关键挑战。
  • 整合和相容性问题：在不同的应用程式和系统之间部署AI视觉晶片时，可能会出现整合和相容性问题。确保晶片与各种硬体和软体平台无缝协作对于成功实施至关重要。应对这些挑战需要仔细的设计和测试互通性。
  • 资料隐私和安全问题：由于AI视觉晶片将用于监控和医疗保健等敏感应用，因此资料隐私和安全问题是关键问题。确保强有力的安全措施和法规遵循对于保护资料和维护用户信任至关重要。解决这些问题对于视觉技术的普及至关重要。

AI视觉晶片市场受到技术进步、自动化需求、家用电器成长、智慧城市发展和边缘运算的影响。然而，它面临着包括高开发成本、整合问题和资料安全问题在内的挑战。平衡这些市场驱动因素和挑战是AI视觉晶片市场持续成长和创新的关键。

目录

第一章执行摘要

第二章 全球AI视觉晶片市场：市场动态

  • 简介、背景和分类
  • 供应链
  • 产业驱动力与挑战

第三章市场趋势与预测分析（2019-2031）

  • 宏观经济趋势（2019-2024）及预测（2025-2031）
  • 全球AI视觉晶片市场趋势（2019-2024）及预测（2025-2031）
  • 全球AI视觉晶片市场类型
    • 12nm
    • 14nm
    • 22nm
    • 其他的
  • 全球AI视觉晶片市场应用状况
    • 安全与监控
    • 车
    • 家电
    • 物联网 (IoT)
    • 无人机
    • 机器人
    • 其他的

第四章区域市场趋势与预测分析（2019-2031）

  • 全球AI视觉晶片市场区域分布
  • 北美AI视觉晶片市场
  • 欧洲AI视觉晶片市场
  • 亚太地区AI视觉晶片市场
  • 其他地区AI视觉晶片市场

第五章 竞争分析

  • 产品系列分析
  • 营运整合
  • 波特五力分析

第六章 成长机会与策略分析

  • 成长机会分析
    • 全球人工智慧视觉晶片市场成长机会（按类型）
    • 全球人工智慧视觉晶片市场按应用分類的成长机会
    • 全球人工智慧视觉晶片市场各区域成长机会
  • 全球AI视觉晶片市场新趋势
  • 战略分析
    • 新产品开发
    • 全球AI视觉晶片市场产能扩张
    • 全球AI视觉晶片市场的企业合併
    • 认证和许可

第七章主要企业简介

  • Ambarella
  • Nextchip
  • Centeye
  • Ambarella
  • Axera
  • Goke Microelectronics
  • PixelCore
  • HiSilicon
  • IMICRO
  • NextVPU
简介目录

The future of the global AI vision chip market looks promising with opportunities in the security & surveillance, automotive, consumer electronic, internet of things, drone, and robot markets. The global AI vision chip market is expected to grow with a CAGR of 32.4% from 2025 to 2031. The major drivers for this market are the growing adoption of edge computing and the rising adoption of computer vision technology in various industries such as manufacturing, healthcare, security, and autonomous vehicles.

  • Lucintel forecasts that, within the type category, 12 nm is expected to witness the highest growth over the forecast period.
  • Within the application category, security & surveillance is expected to witness the highest growth.
  • In terms of regions, APAC is expected to witness the highest growth over the forecast period.

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Emerging Trends in the AI Vision Chip Market

The AI vision chip market is evolving with several key trends that are driving innovation and adoption across various applications.

  • Edge AI Integration: Edge AI integration is a significant trend, enabling AI vision chips to process data locally rather than relying on cloud computing. This reduces latency, enhances real-time processing, and improves privacy by minimizing data transmission. Edge AI chips are crucial for applications such as autonomous vehicles, smart cameras, and industrial automation, where immediate data analysis and response are essential.
  • Enhanced Energy Efficiency: There is a growing emphasis on energy-efficient AI vision chips to address the increasing demand for power in high-performance computing. Advances in chip design and manufacturing technologies are leading to the development of chips that consume less power while delivering high performance. This trend supports the deployment of AI vision chips in battery-powered devices and applications where energy conservation is critical.
  • Increased Focus on Security and Privacy: As AI vision chips are used in sensitive applications like surveillance and personal devices, there is an increased focus on enhancing security and privacy features. Innovations include incorporating advanced encryption and secure data processing capabilities directly into the chips. This trend aims to address concerns about data breaches and unauthorized access, ensuring the secure and reliable operation of vision systems.
  • Integration with 5G Networks: The integration of AI vision chips with 5G networks is enhancing the capabilities of remote and real-time applications. 5G's high-speed connectivity and low latency complement the processing power of AI vision chips, enabling advanced use cases such as real-time remote monitoring, smart city infrastructure, and augmented reality applications. This trend supports the growth of connected devices and applications requiring high-speed data transfer.
  • Growth of AI-Powered Robotics: AI-powered robotics is a key growth area for AI vision chips, as these chips enhance the visual perception and decision-making capabilities of robots. Developments include improved object recognition, depth perception, and navigation capabilities. This trend supports advancements in various robotics applications, including manufacturing, healthcare, and service robots, driving innovation in automation and intelligent systems.

These emerging trends are reshaping the AI vision chip market by enhancing performance, efficiency, and application capabilities. Edge AI integration, energy efficiency, security and privacy, 5G connectivity, and AI-powered robotics are driving innovation and adoption, leading to more advanced and versatile vision systems.

Recent Developments in the AI Vision Chip Market

Recent developments in the AI vision chip market reflect advancements in technology and increasing demand for sophisticated imaging solutions.

  • Introduction of High-Performance Edge AI Chips: New high-performance edge AI chips are being introduced, offering advanced processing capabilities for real-time image analysis. These chips are designed to perform complex tasks locally, reducing latency and enhancing the functionality of applications such as autonomous vehicles and smart cameras. The focus is on improving processing power while maintaining low energy consumption.
  • Advancements in Low-Power AI Vision Chips: Developments in low-power AI vision chips are addressing the need for energy efficiency in battery-operated devices. Innovations include optimizing chip architectures and using advanced manufacturing processes to reduce power consumption without compromising performance. These chips are essential for wearable devices, IoT applications, and portable imaging systems.
  • Enhanced AI Algorithms for Vision Chips: The integration of advanced AI algorithms into vision chips is improving capabilities such as object detection, facial recognition, and scene understanding. These enhancements enable more accurate and sophisticated image processing, supporting applications in security, robotics, and augmented reality. AI-driven improvements are making vision chips more effective in diverse and complex environments.
  • Expansion of AI Vision Chips in Consumer Electronics: AI vision chips are increasingly being integrated into consumer electronics, such as smartphones and smart home devices. Developments include enhancing camera systems with advanced image processing capabilities and enabling new features such as real-time image enhancement and object recognition. This trend reflects the growing demand for intelligent and feature-rich consumer products.
  • Growth in AI Vision Chips for Automotive Applications: The automotive sector is experiencing growth in AI vision chips designed for advanced driver-assistance systems (ADAS) and autonomous vehicles. Innovations include chips that support features such as lane-keeping, collision avoidance, and adaptive cruise control. These developments are driving advancements in automotive safety and automation, reflecting the industry's focus on intelligent transportation solutions.

These key developments highlight the rapid advancements in the AI vision chip market. High-performance edge AI chips, low-power solutions, enhanced AI algorithms, expansion into consumer electronics, and growth in automotive applications are driving innovation and shaping the future of AI vision technologies.

Strategic Growth Opportunities for AI Vision Chip Market

The AI vision chip market presents several strategic growth opportunities across various applications, driven by technological advancements and market demands.

  • Smart Security Systems: The growth of smart security systems offers significant opportunities for AI vision chips. These chips enhance surveillance cameras and security solutions with capabilities such as facial recognition, motion detection, and anomaly detection. The demand for advanced security solutions in residential, commercial, and public sectors is driving growth in this application area.
  • Autonomous Vehicles: Autonomous vehicles are a major growth area for AI vision chips, as these chips are critical for processing visual data used in navigation, obstacle detection, and driver assistance systems. The ongoing development of self-driving technology and advancements in automotive safety features are creating opportunities for AI vision chips in the automotive industry.
  • Industrial Automation: AI vision chips are increasingly being used in industrial automation for applications such as quality control, predictive maintenance, and robotics. These chips improve the accuracy and efficiency of manufacturing processes, driving growth in smart factories and automated production lines. The focus on Industry 4.0 and automation is expanding this market segment.
  • Healthcare and Medical Imaging: The healthcare sector presents opportunities for AI vision chips in medical imaging and diagnostics. These chips enhance imaging systems with capabilities such as improved image quality, real-time analysis, and pattern recognition. The growing demand for advanced diagnostic tools and telemedicine is driving adoption in this application area.
  • Augmented Reality (AR) and Virtual Reality (VR): AI vision chips are crucial for AR and VR applications, providing the processing power needed for immersive experiences and real-time interactions. Developments in AR and VR technologies are creating opportunities for AI vision chips to support applications in gaming, training, and entertainment, enhancing user experiences and expanding market potential.

These strategic growth opportunities highlight the diverse applications and potential of AI vision chips. By focusing on smart security systems, autonomous vehicles, industrial automation, healthcare, and AR/VR, companies can tap into expanding markets and address emerging needs, driving innovation and growth in the AI vision chip sector.

AI Vision Chip Market Driver and Challenges

The AI vision chip market is shaped by various drivers and challenges, including technological advancements, economic factors, and regulatory considerations.

The factors responsible for driving the AI vision chip market include:

  • Technological Advancements: Rapid advancements in AI and vision technologies are driving the AI vision chip market. Innovations in chip design, processing power, and AI algorithms are enhancing the capabilities of vision systems, enabling more sophisticated and efficient applications. These advancements support the growth of AI vision chips across multiple industries.
  • Increasing Demand for Automation: The growing demand for automation in sectors such as manufacturing, automotive, and security is driving the adoption of AI vision chips. These chips enable advanced visual recognition and processing, supporting automation efforts and improving efficiency. The focus on smart factories, autonomous vehicles, and intelligent security systems fuels market growth.
  • Expansion of Consumer Electronics: The integration of AI vision chips into consumer electronics, such as smartphones and smart home devices, is driving market expansion. The demand for enhanced imaging capabilities and intelligent features in consumer products is creating opportunities for AI vision chip manufacturers. This trend reflects the increasing importance of advanced vision technologies in everyday devices.
  • Growth in Smart Cities and Infrastructure: The development of smart cities and infrastructure is creating demand for AI vision chips in applications such as surveillance, traffic management, and public safety. The focus on building intelligent and connected urban environments is driving the adoption of vision chips that support these initiatives, contributing to market growth.
  • Advances in Edge Computing: The rise of edge computing is driving demand for AI vision chips with local processing capabilities. Edge AI chips enable real-time data analysis and response, supporting applications in autonomous vehicles, industrial automation, and smart devices. This trend reflects the growing need for efficient and low-latency computing solutions.

Challenges in the AI vision chip market include:

  • High Development Costs: The development and production of AI vision chips involve high costs related to research, design, and manufacturing. These expenses can be a barrier to entry for new players and impact the affordability of chips for end users. Managing development costs while maintaining competitive pricing is a key challenge for the industry.
  • Integration and Compatibility Issues: Integration and compatibility issues can arise when deploying AI vision chips in diverse applications and systems. Ensuring that chips work seamlessly with different hardware and software platforms is essential for successful implementation. Addressing these challenges requires careful design and testing to achieve interoperability.
  • Data Privacy and Security Concerns: As AI vision chips are used in sensitive applications such as surveillance and healthcare, data privacy and security concerns are significant challenges. Ensuring robust security measures and compliance with regulations is crucial to protect data and maintain user trust. Addressing these concerns is essential for the widespread adoption of vision technologies.

The AI vision chip market is influenced by technological advancements, automation demand, consumer electronics growth, smart city development, and edge computing. However, high development costs, integration issues, and data security concerns present challenges. Balancing these drivers and challenges is crucial for the continued growth and innovation in the AI vision chip market.

List of AI Vision Chip Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies AI vision chip companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the AI vision chip companies profiled in this report include-

  • Ambarella
  • Nextchip
  • Centeye
  • Ambarella
  • Axera
  • Goke Microelectronics
  • PixelCore
  • HiSilicon
  • IMICRO
  • NextVPU

AI Vision Chip by Segment

The study includes a forecast for the global AI vision chip market by type, application, and region.

AI Vision Chip Market by Type [Analysis by Value from 2019 to 2031]:

  • 12 nm
  • 14 nm
  • 22 nm
  • Others

AI Vision Chip Market by Application [Analysis by Value from 2019 to 2031]:

  • Security & Surveillance
  • Automotive
  • Consumer Electronics
  • Internet of Things
  • Drone
  • Robot
  • Others

AI Vision Chip Market by Region [Analysis by Value from 2019 to 2031]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

Country Wise Outlook for the AI Vision Chip Market

The AI vision chip market has experienced significant advancements due to increasing demand for enhanced visual recognition and processing capabilities across various sectors. AI vision chips, which integrate artificial intelligence with imaging technologies, are driving innovations in automation, surveillance, automotive, and consumer electronics. Each country is making strides in this technology, reflecting local priorities and technological expertise.

  • United States: In the U.S., recent developments in AI vision chips include advancements in edge computing and integration with AI platforms for real-time image processing. Companies like Intel and NVIDIA are leading innovations with chips designed for high-performance computer vision tasks, supporting applications in autonomous vehicles, security systems, and augmented reality (AR). The focus is also on enhancing chip efficiency and processing power to meet growing demands in data-intensive applications.
  • China: China is rapidly advancing in the AI vision chip market with significant investments in AI research and development. Chinese tech giants such as Huawei and Alibaba are developing vision chips that enhance capabilities in facial recognition, smart surveillance, and industrial automation. The government's push for technological self-sufficiency and advancements in semiconductor manufacturing is accelerating the deployment of AI vision chips across various sectors, including smart cities and e-commerce.
  • Germany: Germany is focusing on integrating AI vision chips with industrial automation and smart manufacturing. Companies like Bosch and Infineon are developing chips that enhance machine vision systems, enabling precision in manufacturing processes and predictive maintenance. The emphasis is on improving energy efficiency and processing speed to support Germany's strong industrial base and its Industry 4.0 initiatives, driving innovation in smart factories and automation systems.
  • India: In India, the AI vision chip market is growing with applications in security, retail, and healthcare. Indian startups and tech companies are focusing on cost-effective solutions that leverage AI vision chips for surveillance systems, automated retail checkout, and medical imaging. The market is driven by increasing urbanization and the need for advanced technology in growing sectors, along with government initiatives to promote digital transformation and innovation.
  • Japan: Japan is advancing AI vision chips with applications in robotics, consumer electronics, and smart infrastructure. Companies such as Sony and Panasonic are developing chips that enhance image quality and processing capabilities for robotics and smart home devices. Japan's focus on integrating AI with IoT technologies is driving innovations in automation and smart city applications, reflecting the country's commitment to leading in technology and digital transformation.

Features of the Global AI Vision Chip Market

Market Size Estimates: AI vision chip market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: AI vision chip market size by type, application, and region in terms of value ($B).

Regional Analysis: AI vision chip market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the AI vision chip market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the AI vision chip market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the AI vision chip market by type (12 nm, 14 nm, 22 nm, and others), application (security & surveillance, automotive, consumer electronics, internet of things, drone, robot, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global AI Vision Chip Market : Market Dynamics

  • 2.1: Introduction, Background, and Classifications
  • 2.2: Supply Chain
  • 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

  • 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
  • 3.2. Global AI Vision Chip Market Trends (2019-2024) and Forecast (2025-2031)
  • 3.3: Global AI Vision Chip Market by Type
    • 3.3.1: 12 nm
    • 3.3.2: 14 nm
    • 3.3.3: 22 nm
    • 3.3.4: Others
  • 3.4: Global AI Vision Chip Market by Application
    • 3.4.1: Security & Surveillance
    • 3.4.2: Automotive
    • 3.4.3: Consumer Electronics
    • 3.4.4: Internet of Things
    • 3.4.5: Drone
    • 3.4.6: Robot
    • 3.4.7: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

  • 4.1: Global AI Vision Chip Market by Region
  • 4.2: North American AI Vision Chip Market
    • 4.2.1: North American Market by Type: 12 nm, 14 nm, 22 nm, and Others
    • 4.2.2: North American Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
  • 4.3: European AI Vision Chip Market
    • 4.3.1: European Market by Type: 12 nm, 14 nm, 22 nm, and Others
    • 4.3.2: European Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
  • 4.4: APAC AI Vision Chip Market
    • 4.4.1: APAC Market by Type: 12 nm, 14 nm, 22 nm, and Others
    • 4.4.2: APAC Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
  • 4.5: ROW AI Vision Chip Market
    • 4.5.1: ROW Market by Type: 12 nm, 14 nm, 22 nm, and Others
    • 4.5.2: ROW Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others

5. Competitor Analysis

  • 5.1: Product Portfolio Analysis
  • 5.2: Operational Integration
  • 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

  • 6.1: Growth Opportunity Analysis
    • 6.1.1: Growth Opportunities for the Global AI Vision Chip Market by Type
    • 6.1.2: Growth Opportunities for the Global AI Vision Chip Market by Application
    • 6.1.3: Growth Opportunities for the Global AI Vision Chip Market by Region
  • 6.2: Emerging Trends in the Global AI Vision Chip Market
  • 6.3: Strategic Analysis
    • 6.3.1: New Product Development
    • 6.3.2: Capacity Expansion of the Global AI Vision Chip Market
    • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global AI Vision Chip Market
    • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

  • 7.1: Ambarella
  • 7.2: Nextchip
  • 7.3: Centeye
  • 7.4: Ambarella
  • 7.5: Axera
  • 7.6: Goke Microelectronics
  • 7.7: PixelCore
  • 7.8: HiSilicon
  • 7.9: IMICRO
  • 7.10: NextVPU