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市場調查報告書
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1457032

機器學習處理器市場 – 2024 年至 2029 年預測

Machine Learning Processor Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 138 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

2022 年機器學習處理器市值為 38.43 億美元，複合年成長率為 19.94%，到 2029 年市場規模將達到 139.17 億美元。

由於人工智慧的普及和巨量資料的趨勢，全球機器學習處理器市場正在不斷成長。物聯網設備的增加進一步推動了對機器學習處理器的需求並推動市場成長。人工智慧應用的增加、電腦能力的增強和硬體成本的降低正在推動機器學習處理器的銷售。各行業自動化目的人工智慧的高採用率正在推動機器學習處理器市場的發展。目前，所有技術來源產生的資料量不斷增加，對機器學習處理器執行更快、更進階分析的需求不斷增加。公司正在大力投資研發並推出新的和更新的產品，以佔領更大的市場佔有率。機器學習處理器透過改善消費者服務和降低營運成本顯著推動市場成長。

然而，技術純熟勞工的缺乏以及標準和通訊協定的缺乏正在限制機器學習處理器的市場成長。人工智慧是一個複雜的系統，需要熟練的員工來開發、管理和部署。

市場促進因素：

  • 更多採用機器學習 (ML) 和人工智慧 (AI) 技術。

機器學習處理器市場受到人工智慧（AI）和機器學習（ML）技術日益廣泛使用的顯著影響。隨著各行各業的公司將機器學習和人工智慧融入業務中，對能夠有效處理影像識別、自然語言處理和預測分析等工作負載的運算複雜性的專用處理器的需求不斷成長。與傳統處理器相比，機器學習處理器是專用為機器學習演算法中使用的矩陣計算和平行處理而設計的。這可以實現更快、更有效的模型推理和訓練。

  • 人工智慧模型的複雜性。

機器學習處理器市場受到機器學習 (ML) 模型日益複雜性的顯著影響，需要改善硬體架構和功能。隨著機器學習(ML) 模型，尤其是使用深度學習的模型變得更加詳細和複雜，它們需要更高的運算能力來有效地執行學習和推理的複雜數學運算，因此對處理器的需求不斷成長。 GPU、TPU 和其他加速器等專用硬體設計已被創建來滿足這一需求。這些架構是專門為處理與大規模機器學習模型相關的複雜矩陣運算和平行性而建構的。市場反應（包括具有多核心和並行處理單元的處理器）顯示更加重視並行計算的最佳化。

  • GPU預計將佔據很大的市場佔有率

GPU（圖形處理單元）擴大用於遊戲和影片觀看。擴增實境 (AR) 等不斷發展的新技術正在推動市場對 GPU 處理器的需求。由於量子運算使用量的增加，預計 CPU 在預測期間內將出現合理的複合年成長率。量子計算可以讓需要數千年的計算在短短幾秒鐘內完成。 FPGA 正在推動機器學習處理器市場。新的先進技術每年都會出現，人們不斷更新以適應時代的潮流。 ASIC 處理器擴大應用於各個行業，根據行業需求執行特定任務，對市場成長產生積極影響。

從技術角度來看，系統晶片預計將成為主要細分市場之一。

由於智慧型手機市場的擴張，晶片系統在全球機器學習處理器市場中佔有顯著佔有率。晶片系統單晶片、記憶體、輸入/輸出埠、輔助記憶體等整合在單一硬幣大小的基板或微處理器上，使其成為智慧型手機的理想選擇。晶片系統晶片通常用於智慧型手機，以提高效能並更快地處理多任務活動。由於系統級封裝用於 3D 開發，因此擴大推動機器學習處理器市場的發展。市場參與企業擴大投資這項技術，應用範圍也從智慧型手機和媒體參與企業擴展到更廣泛的行業領域。由於該技術比許多其他技術支援更廣泛的整合技術，因此尋求解決方案彈性的最終用戶不斷增加對該技術的採用，從而推動市場成長。

消費性電子預計將成為參與企業機器學習處理器市場的關鍵產業之一。

預計消費電子產品領域將在預測期內佔據重要的市場佔有率。技術進步正在為具有改進應用程式的更好設備創造市場。科技的未來依賴人工智慧和巨量資料的持續使用。企業正在智慧型手機中使用機器學習處理器來解鎖更多功能和功能，例如更快的處理器和增強的多任務處理能力。智慧型手機和平板電腦正在融入人工智慧，以改善客戶體驗並創建更好的使用者介面。因此，對先進消費性電子產品不斷成長的需求正在推動對機器學習處理器的需求。由於醫療、通訊和技術領域擴大使用先進技術，機器學習處理器的使用正在增加。由於全球電子商務行業的蓬勃發展，預計零售業在預測期內將出現顯著的市場成長。

按地區分類，北美預計將成為最大的市場。

按地區分類，全球機器學習處理器市場分為北美、南美、歐洲、中東和非洲以及亞太地區。由於先進技術的早期採用和大型市場參與企業的存在，預計北美將在全球機器學習處理器市場中佔據重要佔有率。在該地區營運的全球軟體和硬體公司擴大利用人工智慧、巨量資料和增強智慧來改進技術並更好地服務客戶。預計在預測期內，對人工智慧的高投資將進一步推動該地區機器學習處理器市場的成長。

主要進展：

  • 2023 年 10 月，領先的創新半導體技術製造商瑞薩電子公司與領先的節能邊緣人工智慧 (AI) 處理系統供應商 EdgeCortix 結成策略聯盟。瑞薩電子正在為 EdgeCortix 的最新一輪資金籌措以及戰略合作夥伴關係做出貢獻。此次合作和投資將使瑞薩電子能夠獨家獲得 EdgeCortix 的最尖端科技。

目錄

第1章 簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關利益者的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現
  • CXO觀點

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章機器學習處理器市場：按處理器類型

  • 介紹
  • 圖形處理器
  • ASIC
  • CPU
  • FPGA

第6章機器學習處理器市場：依技術分類

  • 介紹
  • 處理器系統 (SIC)
  • 系統級封裝(SIP)
  • 多處理器模組
  • 其他

第7章機器學習處理器市場：按行業

  • 介紹
  • 家用電器
  • 通訊科技
  • 零售
  • 醫療保健
  • 車
  • 其他

第8章機器學習處理器市場：按地區

  • 介紹
  • 北美洲
  • 南美洲
  • 歐洲
  • 中東/非洲
  • 亞太地區

第9章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第10章 公司簡介

  • ARM Limited
  • NVIDIA Corporation
  • Samsung
  • Amazon
  • Intel
  • Qualcomm
  • IBM
  • Apple
簡介目錄
Product Code: KSI061611688

The machine learning processor market is evaluated at US$3.843 billion for the year 2022 growing at a CAGR of 19.94% reaching the market size of US$13.917 billion by the year 2029.

The global machine learning processor market is rising due to the growing popularity of artificial intelligence and the trend toward big data. Increasing IoT devices is further driving the demand for machine learning processors, thereby driving market growth. The increasing number of AI applications, improved computer power, and falling hardware costs are driving machine learning processor sales. The high adoption of artificial intelligence by various industries for automation purposes is driving the market for machine learning processors. The increasing amount of data generated nowadays from all technical sources is growing the requirement for faster and more advanced machine learning processors for faster analysis. Companies are heavily investing in research and development to introduce new and updated products to occupy a larger market share. The machine learning processor is improving consumer services and reducing operational costs, which are significantly driving the market growth.

However, the lack of a skilled workforce and the absence of standards and protocols are restraining the market growth of machine learning processors. AI is a complex system, and developing, managing, and implementing, it requires employees with certain skill sets.

MARKET DRIVERS:

  • Increasing adoption of machine learning (ML) and artificial intelligence (AI) technologies.

The machine learning processors market is greatly impacted by the growing use of artificial intelligence (AI) and machine learning (ML) technologies. The need for specialized processors that can effectively handle the computational complexities of workloads like image recognition, natural language processing, and predictive analytics is growing as companies in a variety of industries incorporate ML and AI into their operations. Machine learning processors, as opposed to conventional processors, are designed expressly for the matrix computations and parallel processing used in machine learning algorithms. This allows for quicker and more effective model inference and training.

  • Rising complexity of AI Models.

The machine learning processors market is significantly impacted by the growing complexity of machine learning (ML) models, which calls for improvements in hardware architecture and capabilities. To effectively perform complicated mathematical operations during both training and inference, there is an increasing demand for processors that can supply increased computing capacity as machine learning (ML) models, especially those using deep learning, get more detailed and advanced. Owing to this need, specialized hardware designs have been created, including GPUs, TPUs, and other accelerators. These architectures are made expressly to handle the complicated matrix operations and parallel processing that come with large-scale machine-learning models. The market's reaction, which includes processors with many cores and parallel processing units, demonstrates a greater emphasis on optimization for parallel computing.

  • GPU is anticipated to have a significant share of the market

GPU (graphics processing units) are increasingly being used for gaming and video viewing purposes. Advancing and new technology like AR (Augmented Reality) are driving the demand for GPU processors in the market. The CPU is expected to witness a decent CAGR during the forecast period due to the increasing use of Quantum computing. Quantum computing takes only a few seconds to complete a calculation that otherwise may take thousands of years. The FPGA is driving the machine learning processor market as new and advanced technology is coming every year and people are continuously updating according to the current trend, and the FPGA processor makes it faster to configure. ASIC processors are increasingly being used by different industries for carrying out specific tasks according to the requirements of the industry, thereby positively impacting market growth.

By technology, System-On-Chip is anticipated to be one of the major segments.s

System-on-chip has a noteworthy share in the global machine learning processor market on account of the growing market for smartphones. System-On-Chip includes a central processing unit, memory, input/output ports, and secondary storage, all on a single substrate or microprocessor, the size of a coin, which is perfectly suitable for smartphones. System-on-chip is usually used in smartphones for better performance and faster processing of multi-task activities. System-in-package is increasingly boosting the market for machine learning processors due to its usage in 3D development. The heavy inflow of investments by market players into this technology is expanding its scope of application from smartphones and media players to many more applications across a wider range of industries. Since this technology supports a wider range of integration techniques than many other technologies, end-users seeking more flexibility in solutions are showing a continuously increasing adoption of this technology, thus fueling the market growth.

Consumer Electronics is predicted to be one of the major industries for machine learning processor market players.

The consumer electronics segment is predicted to account for a significant market share during the forecast period. The increasing advancement in technology is building the market for better devices with improved applications. The future of technology is dependent on the increasing use of artificial intelligence and big data. Companies are using a machine learning processor in smartphones to improve their features and maximize capabilities, like a faster processor and improved multi-tasking ability. Smartphones and tablets are embedded with artificial intelligence to enhance customer experience and a better user interface. Hence, the growing demand for advanced consumer electronics is spurring the demand for machine learning processors. Increased usage of advanced technologies in healthcare and communication & technology is giving rise to the use of machine learning processors as new devices are highly embedded with machine learning processors for better performance. The retail sector is expected to experience significant market growth during the forecast period owing to the booming global e-commerce industry.

By geography, North America is anticipated to be the largest market.

Regionally, the global machine learning processor market is classified into North America, South America, Europe, the Middle East and Africa, and the Asia Pacific. North America is expected to have a notable market share in the global machine learning processor market owing to the early adoption of advanced technologies and the presence of major market players in the region. Global software and hardware companies present in this region are increasingly using artificial intelligence, big data, and augmented reality to improve technology and provide better services to customers. High investments in artificial intelligence will further bolster the market growth of machine learning processors across this region throughout the forecast period.

Key Developments:

  • In October 2023, a strategic alliance was established between Renesas Electronics Corporation, a leading producer of innovative semiconductor technologies, and EdgeCortix, a top supplier of edge Artificial Intelligence (AI) processing systems that are energy-efficient. Renesas has contributed to EdgeCortix's most recent fundraising round in tandem with the strategic partnership. Through this collaboration and investment, EdgeCortix will provide Renesas exclusive access to its cutting-edge technology.

Segmentation:

By Processor Type

  • GPU
  • ASIC
  • CPU
  • FPGA

By Technology

  • System-On-Processor (SIC)
  • System-IN-Package (SIP)
  • Multi-Processor Module
  • Others

By Industry Vertical

  • Consumer Electronics
  • Communication & Technology
  • Retail
  • Healthcare
  • Automotive
  • Others

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • Israel
  • UAE
  • Others
  • Asia Pacific
  • China
  • Japan
  • South Korea
  • India
  • Thailand
  • Taiwan
  • Indonesia
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline
  • 1.8. Key Benefits to the stakeholder

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Processes

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings
  • 3.2. CXO Perspective

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. MACHINE LEARNING PROCESSOR MARKET, BY PROCESSOR TYPE

  • 5.1. Introduction
  • 5.2. GPU
    • 5.2.1. Market Trends and Opportunities
    • 5.2.2. Growth Prospects
    • 5.2.3. Geographic Lucrativeness
  • 5.3. ASIC
    • 5.3.1. Market Trends and Opportunities
    • 5.3.2. Growth Prospects
    • 5.3.3. Geographic Lucrativeness
  • 5.4. CPU
    • 5.4.1. Market Trends and Opportunities
    • 5.4.2. Growth Prospects
    • 5.4.3. Geographic Lucrativeness
  • 5.5. FPGA
    • 5.5.1. Market Trends and Opportunities
    • 5.5.2. Growth Prospects
    • 5.5.3. Geographic Lucrativeness

6. MACHINE LEARNING PROCESSOR MARKET, BY TECHNOLOGY

  • 6.1. Introduction
  • 6.2. System-on-Processor (SIC)
    • 6.2.1. Market Trends and Opportunities
    • 6.2.2. Growth Prospects
    • 6.2.3. Geographic Lucrativeness
  • 6.3. System-in-Package (SIP)
    • 6.3.1. Market Trends and Opportunities
    • 6.3.2. Growth Prospects
    • 6.3.3. Geographic Lucrativeness
  • 6.4. Multi-Processor Module
    • 6.4.1. Market Trends and Opportunities
    • 6.4.2. Growth Prospects
    • 6.4.3. Geographic Lucrativeness
  • 6.5. Others
    • 6.5.1. Market Trends and Opportunities
    • 6.5.2. Growth Prospects
    • 6.5.3. Geographic Lucrativeness

7. MACHINE LEARNING PROCESSOR MARKET, BY INDUSTRY VERTICAL

  • 7.1. Introduction
  • 7.2. Consumer Electronics
    • 7.2.1. Market Trends and Opportunities
    • 7.2.2. Growth Prospects
    • 7.2.3. Geographic Lucrativeness
  • 7.3. Communication & Technology
    • 7.3.1. Market Trends and Opportunities
    • 7.3.2. Growth Prospects
    • 7.3.3. Geographic Lucrativeness
  • 7.4. Retail
    • 7.4.1. Market Trends and Opportunities
    • 7.4.2. Growth Prospects
    • 7.4.3. Geographic Lucrativeness
  • 7.5. Healthcare
    • 7.5.1. Market Trends and Opportunities
    • 7.5.2. Growth Prospects
    • 7.5.3. Geographic Lucrativeness
  • 7.6. Automotive
    • 7.6.1. Market Trends and Opportunities
    • 7.6.2. Growth Prospects
    • 7.6.3. Geographic Lucrativeness
  • 7.7. Others
    • 7.7.1. Market Trends and Opportunities
    • 7.7.2. Growth Prospects
    • 7.7.3. Geographic Lucrativeness

8. MACHINE LEARNING PROCESSOR MARKET, BY GEOGRAPHY

  • 8.1. Introduction
  • 8.2. North America
    • 8.2.1. By Processor Type
    • 8.2.2. By Technology
    • 8.2.3. By Industry Vertical
    • 8.2.4. By Country
      • 8.2.4.1. USA
        • 8.2.4.1.1. Market Trends and Opportunities
        • 8.2.4.1.2. Growth Prospects
      • 8.2.4.2. Canada
        • 8.2.4.2.1. Market Trends and Opportunities
        • 8.2.4.2.2. Growth Prospects
      • 8.2.4.3. Mexico
        • 8.2.4.3.1. Market Trends and Opportunities
        • 8.2.4.3.2. Growth Prospects
  • 8.3. South America
    • 8.3.1. By Processor Type
    • 8.3.2. By Technology
    • 8.3.3. By Industry Vertical
    • 8.3.4. By Country
      • 8.3.4.1. Brazil
        • 8.3.4.1.1. Market Trends and Opportunities
        • 8.3.4.1.2. Growth Prospects
      • 8.3.4.2. Argentina
        • 8.3.4.2.1. Market Trends and Opportunities
        • 8.3.4.2.2. Growth Prospects
      • 8.3.4.3. Others
        • 8.3.4.3.1. Market Trends and Opportunities
        • 8.3.4.3.2. Growth Prospects
  • 8.4. Europe
    • 8.4.1. By Processor Type
    • 8.4.2. By Technology
    • 8.4.3. By Industry Vertical
    • 8.4.4. By Country
      • 8.4.4.1. Germany
        • 8.4.4.1.1. Market Trends and Opportunities
        • 8.4.4.1.2. Growth Prospects
      • 8.4.4.2. France
        • 8.4.4.2.1. Market Trends and Opportunities
        • 8.4.4.2.2. Growth Prospects
      • 8.4.4.3. United Kingdom
        • 8.4.4.3.1. Market Trends and Opportunities
        • 8.4.4.3.2. Growth Prospects
      • 8.4.4.4. Spain
        • 8.4.4.4.1. Market Trends and Opportunities
        • 8.4.4.4.2. Growth Prospects
      • 8.4.4.5. Others
        • 8.4.4.5.1. Market Trends and Opportunities
        • 8.4.4.5.2. Growth Prospects
  • 8.5. Middle East and Africa
    • 8.5.1. By Processor Type
    • 8.5.2. By Technology
    • 8.5.3. By Industry Vertical
    • 8.5.4. By Country
      • 8.5.4.1. Saudi Arabia
        • 8.5.4.1.1. Market Trends and Opportunities
        • 8.5.4.1.2. Growth Prospects
      • 8.5.4.2. UAE
        • 8.5.4.2.1. Market Trends and Opportunities
        • 8.5.4.2.2. Growth Prospects
      • 8.5.4.3. Israel
        • 8.5.4.3.1. Market Trends and Opportunities
        • 8.5.4.3.2. Growth Prospects
      • 8.5.4.4. Others
        • 8.5.4.4.1. Market Trends and Opportunities
        • 8.5.4.4.2. Growth Prospects
  • 8.6. Asia Pacific
    • 8.6.1. By Processor Type
    • 8.6.2. By Technology
    • 8.6.3. By Industry Vertical
    • 8.6.4. By Country
      • 8.6.4.1. China
        • 8.6.4.1.1. Market Trends and Opportunities
        • 8.6.4.1.2. Growth Prospects
      • 8.6.4.2. Japan
        • 8.6.4.2.1. Market Trends and Opportunities
        • 8.6.4.2.2. Growth Prospects
      • 8.6.4.3. South Korea
        • 8.6.4.3.1. Market Trends and Opportunities
        • 8.6.4.3.2. Growth Prospects
      • 8.6.4.4. India
        • 8.6.4.4.1. Market Trends and Opportunities
        • 8.6.4.4.2. Growth Prospects
      • 8.6.4.5. Thailand
        • 8.6.4.5.1. Market Trends and Opportunities
        • 8.6.4.5.2. Growth Prospects
      • 8.6.4.6. Indonesia
        • 8.6.4.6.1. Market Trends and Opportunities
        • 8.6.4.6.2. Growth Prospects
      • 8.6.4.7. Taiwan
        • 8.6.4.7.1. Market Trends and Opportunities
        • 8.6.4.7.2. Growth Prospects
      • 8.6.4.8. Others
        • 8.6.4.8.1. Market Trends and Opportunities
        • 8.6.4.8.2. Growth Prospects

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. ARM Limited
  • 10.2. NVIDIA Corporation
  • 10.3. Samsung
  • 10.4. Amazon
  • 10.5. Intel
  • 10.6. Qualcomm
  • 10.7. IBM
  • 10.8. Apple