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市场调查报告书
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1457032

机器学习处理器市场 – 2024 年至 2029 年预测

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个工作天内

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简介目录

2022 年机器学习处理器市值为 38.43 亿美元，复合年增长率为 19.94%，到 2029 年市场规模将达到 139.17 亿美元。

由于人工智慧的普及和巨量资料的趋势，全球机器学习处理器市场正在不断增长。物联网设备的增加进一步推动了对机器学习处理器的需求并推动市场成长。人工智慧应用的增加、电脑能力的增强和硬体成本的降低正在推动机器学习处理器的销售。各行业自动化目的人工智慧的高采用率正在推动机器学习处理器市场的发展。目前，所有技术来源产生的资料量不断增加，对机器学习处理器执行更快、更进阶分析的需求不断增加。公司正在大力投资研发并推出新的和更新的产品，以占领更大的市场占有率。机器学习处理器透过改善消费者服务和降低营运成本显着推动市场成长。

然而，技术纯熟劳工的缺乏以及标准和通讯协定的缺乏正在限制机器学习处理器的市场成长。人工智慧是一个复杂的系统，需要熟练的员工来开发、管理和部署。

市场驱动因素：

  • 更多采用机器学习 (ML) 和人工智慧 (AI) 技术。

机器学习处理器市场受到人工智慧（AI）和机器学习（ML）技术日益广泛使用的显着影响。随着各行各业的公司将机器学习和人工智慧融入业务中，对能够有效处理影像识别、自然语言处理和预测分析等工作负载的运算复杂性的专用处理器的需求不断增长。与传统处理器相比，机器学习处理器是专用为机器学习演算法中使用的矩阵计算和平行处理而设计的。这可以实现更快、更有效的模型推理和训练。

  • 人工智慧模型的复杂性。

机器学习处理器市场受到机器学习 (ML) 模型日益复杂性的显着影响，需要改善硬体架构和功能。随着机器学习(ML) 模型，尤其是使用深度学习的模型变得更加详细和复杂，它们需要更高的运算能力来有效地执行学习和推理的复杂数学运算，因此对处理器的需求不断增长。 GPU、TPU 和其他加速器等专用硬体设计已被创建来满足这一需求。这些架构是专门为处理与大规模机器学习模型相关的复杂矩阵运算和平行性而建构的。市场反应（包括具有多核心和并行处理单元的处理器）显示更加重视并行计算的最佳化。

  • GPU预计将占据很大的市场份额

GPU（图形处理单元）越来越多地用于游戏和影片观看。扩增实境 (AR) 等不断发展的新技术正在推动市场对 GPU 处理器的需求。由于量子运算使用量的增加，预计 CPU 在预测期间内将出现合理的复合年增长率。量子计算可以让需要数千年的计算在短短几秒钟内完成。 FPGA 正在推动机器学习处理器市场。新的先进技术每年都会出现，人们不断更新以适应时代的潮流。 ASIC 处理器越来越多地应用于各个行业，根据行业需求执行特定任务，对市场成长产生积极影响。

从技术角度来看，系统晶片预计将成为主要细分市场之一。

由于智慧型手机市场的扩张，晶片系统在全球机器学习处理器市场中占有显着份额。晶片系统单晶片、记忆体、输入/输出埠、辅助记忆体等整合在单一硬币大小的基板或微处理器上，使其成为智慧型手机的理想选择。晶片系统晶片通常用于智慧型手机，以提高效能并更快地处理多任务活动。由于系统级封装用于 3D 开发，因此越来越多地推动机器学习处理器市场的发展。市场参与企业越来越多地投资这项技术，应用范围也从智慧型手机和媒体参与企业扩展到更广泛的行业领域。由于该技术比许多其他技术支援更广泛的整合技术，因此寻求解决方案弹性的最终用户不断增加对该技术的采用，从而推动市场成长。

消费性电子预计将成为参与企业机器学习处理器市场的关键产业之一。

预计消费电子产品领域将在预测期内占据重要的市场占有率。技术进步正在为具有改进应用程式的更好设备创造市场。科技的未来依赖人工智慧和巨量资料的持续使用。企业正在智慧型手机中使用机器学习处理器来解锁更多功能和功能，例如更快的处理器和增强的多任务处理能力。智慧型手机和平板电脑正在融入人工智慧，以改善客户体验并创建更好的使用者介面。因此，对先进消费性电子产品不断增长的需求正在推动对机器学习处理器的需求。由于医疗、通讯和技术领域越来越多地使用先进技术，机器学习处理器的使用正在增加。由于全球电子商务行业的蓬勃发展，预计零售业在预测期内将出现显着的市场成长。

按地区划分，北美预计将成为最大的市场。

按地区划分，全球机器学习处理器市场分为北美、南美、欧洲、中东和非洲以及亚太地区。由于先进技术的早期采用和大型市场参与企业的存在，预计北美将在全球机器学习处理器市场中占据重要份额。在该地区运营的全球软体和硬体公司越来越多地利用人工智慧、巨量资料和增强智慧来改进技术并更好地服务客户。预计在预测期内，对人工智慧的高投资将进一步推动该地区机器学习处理器市场的成长。

主要进展：

  • 2023 年 10 月，领先的创新半导体技术製造商瑞萨电子公司与领先的节能边缘人工智慧 (AI) 处理系统供应商 EdgeCortix 结成策略联盟。瑞萨电子正在为 EdgeCortix 的最新一轮资金筹措以及战略合作伙伴关係做出贡献。此次合作和投资将使瑞萨电子能够独家获得 EdgeCortix 的最尖端科技。

目录

第一章 简介

  • 市场概况
  • 市场定义
  • 调查范围
  • 市场区隔
  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关利益者的主要利益

第二章调查方法

  • 研究设计
  • 调查过程

第三章执行摘要

  • 主要发现
  • CXO观点

第四章市场动态

  • 市场驱动因素
  • 市场限制因素
  • 波特五力分析
  • 产业价值链分析
  • 分析师观点

第五章机器学习处理器市场：按处理器类型

  • 介绍
  • 图形处理器
  • ASIC
  • CPU
  • FPGA

第六章机器学习处理器市场：依技术分类

  • 介绍
  • 处理器系统 (SIC)
  • 系统级封装(SIP)
  • 多处理器模组
  • 其他的

第七章机器学习处理器市场：按行业

  • 介绍
  • 家用电器
  • 通讯科技
  • 零售
  • 医疗保健
  • 车
  • 其他的

第八章机器学习处理器市场：按地区

  • 介绍
  • 北美洲
  • 南美洲
  • 欧洲
  • 中东/非洲
  • 亚太地区

第九章竞争环境及分析

  • 主要企业及策略分析
  • 市场占有率分析
  • 合併、收购、协议和合作
  • 竞争对手仪表板

第十章 公司简介

  • ARM Limited
  • NVIDIA Corporation
  • Samsung
  • Amazon
  • Intel
  • Qualcomm
  • IBM
  • Apple
简介目录
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