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市場調查報告書
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1680469

AI視覺晶片市場報告：趨勢、預測與競爭分析（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個工作天內

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簡介目錄

全球AI視覺晶片市場前景廣闊，在安防、汽車、家電、物聯網、無人機、機器人等市場都存在發展機會。預計全球人工智慧視覺晶片市場從 2025 年到 2031 年的複合年成長率將達到 32.4%。該市場的主要驅動力是邊緣運算的日益普及以及電腦視覺技術在製造業、醫療保健、安全和自動駕駛汽車等各個行業中的日益普及。

  • Lucintel 預測，按類型分類，12nm 將在預測期內達到最高成長。
  • 從應用角度來看，安全和監控預計將實現最高成長。
  • 根據地區來看，預計亞太地區將在預測期內實現最高成長。

AI視覺晶片市場的策略性成長機會

AI視覺晶片市場受技術進步和市場需求驅動，在各個應用領域呈現出若干策略成長機會。

  • 智慧安防系統：智慧安防系統的成長為AI視覺晶片提供了巨大的機會。這些晶片透過臉部辨識、運動偵測和異常偵測等功能增強了監視錄影機和安全解決方案。住宅、商業和公共部門對先進安全解決方案的需求正在推動這一應用領域的成長。
  • 自動駕駛汽車：自動駕駛汽車是人工智慧視覺晶片的主要成長領域。這些晶片對於處理導航、障礙物偵測和駕駛輔助系統中使用的視覺資料至關重要。自動駕駛技術的不斷發展和汽車安全功能的進步為汽車行業的人工智慧視覺晶片創造了機會。
  • 工業自動化：人工智慧視覺晶片擴大用於工業自動化，例如品管、預測性維護和機器人等應用。這些晶片提高了製造過程的精度和效率，推動了智慧工廠和自動化生產線的發展。對工業 4.0 和自動化的關注正在擴大這一細分市場。
  • 醫療保健和醫學影像：在醫療保健領域，人工智慧視覺晶片在醫學影像處理和診斷方面存在機會。這些晶片增強了影像處理系統的功能，例如提高影像品質、即時分析和模式識別。對先進診斷工具和遠端醫療日益成長的需求正在推動這一應用領域的應用。
  • 擴增實境(AR) 和虛擬實境 (VR)：AI 視覺晶片對於 AR 和 VR 應用至關重要，可提供沉浸式體驗和即時互動所需的處理能力。新興國家AR、VR技術市場的發展，為AI視覺晶片創造機會，支援遊戲、訓練、娛樂等應用，提升使用者體驗，擴大市場潛力。

這些策略成長機會凸顯了人工智慧視覺晶片的多樣化應用和潛力。專注於智慧安全系統、自動駕駛汽車、工業自動化、醫療和AR/VR將使公司能夠接觸不斷擴大的市場並滿足新的需求，從而推動AI視覺晶片領域的創新和成長。

AI視覺晶片市場促進因素與挑戰

AI視覺晶片市場受到各種促進因素​​和挑戰的影響，包括技術進步、經濟因素和監管考慮。

AI視覺晶片市場受以下因素驅動：

  • 技術進步：人工智慧和視覺技術的快速進步正在推動人工智慧視覺晶片市場的發展。晶片設計、處理能力和人工智慧演算法的創新正在增強視覺系統的功能，從而實現更先進、更有效率的應用。這些進步正在支援多個行業的人工智慧視覺晶片的發展。
  • 自動化需求不斷成長：製造業、汽車業和安全業等行業對自動化的需求不斷成長，推動了人工智慧視覺晶片的採用。這些晶片實現了先進的視覺識別和處理，支援自動化工作並提高效率。對智慧工廠、自動駕駛汽車和智慧安全系統的關注正在推動市場成長。
  • 家用電子電器的擴張：AI視覺晶片與智慧型手機、智慧家居設備等家用電子電器的整合正在推動市場擴張。消費性產品對增強影像處理和智慧功能的需求正在為AI視覺晶片製造商創造機會。這一趨勢反映了先進視覺技術在日常設備中日益成長的重要性。
  • 智慧城市和基礎設施的成長：智慧城市和基礎設施的發展正在創造對用於監控、交通管理和公共等應用的人工智慧視覺晶片的需求。對創建智慧互聯城市環境的關注正在推動視覺晶片的應用來支持這些努力，從而促進市場成長。
  • 邊緣運算的進步：邊緣運算的興起正在推動對具有本地處理能力的人工智慧視覺晶片的需求。邊緣AI晶片可實現即時資料分析和回應，支援自動駕駛汽車、工業自動化和智慧型裝置中的應用。這一趨勢反映了對高效、低延遲運算解決方案日益成長的需求。

AI視覺晶片市場面臨的挑戰有：

  • 開發成本高：AI視覺晶片的開發和生產涉及研究、設計和製造相關的高成本。這些成本為新參與企業設定了進入壁壘，並影響了最終用戶對晶片的承受能力。管理開發成本並保持有競爭力的價格是該行業面臨的關鍵挑戰。
  • 整合和相容性問題：在不同的應用程式和系統之間部署AI視覺晶片時，可能會出現整合和相容性問題。確保晶片與各種硬體和軟體平台無縫協作對於成功實施至關重要。應對這些挑戰需要仔細的設計和測試互通性。
  • 資料隱私和安全問題：由於AI視覺晶片將用於監控和醫療保健等敏感應用，因此資料隱私和安全問題是關鍵問題。確保強力的安全措施和法規遵循對於保護資料和維護用戶信任至關重要。解決這些問題對於視覺技術的普及至關重要。

AI視覺晶片市場受到技術進步、自動化需求、家用電器成長、智慧城市發展和邊緣運算的影響。然而，它面臨著包括高開發成本、整合問題和資料安全問題在內的挑戰。平衡這些市場促進因素和挑戰是AI視覺晶片市場持續成長和創新的關鍵。

目錄

第1章執行摘要

第2章 全球AI視覺晶片市場：市場動態

  • 簡介、背景和分類
  • 供應鏈
  • 產業驅動力與挑戰

第3章市場趨勢與預測分析（2019-2031）

  • 宏觀經濟趨勢（2019-2024）及預測（2025-2031）
  • 全球AI視覺晶片市場趨勢（2019-2024）及預測（2025-2031）
  • 全球AI視覺晶片市場類型
    • 12nm
    • 14nm
    • 22nm
    • 其他
  • 全球AI視覺晶片市場應用狀況
    • 安全與監控
    • 車
    • 家電
    • 物聯網 (IoT)
    • 無人機
    • 機器人
    • 其他

第4章區域市場趨勢與預測分析（2019-2031）

  • 全球AI視覺晶片市場區域分佈
  • 北美AI視覺晶片市場
  • 歐洲AI視覺晶片市場
  • 亞太地區AI視覺晶片市場
  • 其他地區AI視覺晶片市場

第5章 競爭分析

  • 產品系列分析
  • 營運整合
  • 波特五力分析

第6章 成長機會與策略分析

  • 成長機會分析
    • 全球人工智慧視覺晶片市場成長機會（按類型）
    • 全球人工智慧視覺晶片市場按應用分類的成長機會
    • 全球人工智慧視覺晶片市場各區域成長機會
  • 全球AI視覺晶片市場新趨勢
  • 戰略分析
    • 新產品開發
    • 全球AI視覺晶片市場產能擴張
    • 全球AI視覺晶片市場的企業合併
    • 認證和許可

第7章主要企業簡介

  • Ambarella
  • Nextchip
  • Centeye
  • Ambarella
  • Axera
  • Goke Microelectronics
  • PixelCore
  • HiSilicon
  • IMICRO
  • NextVPU
簡介目錄

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