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IoT 人工智能边缘运算

市场调查报告书

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1529362

全球边缘人工智慧处理器市场 - 2024-2031

Global Edge AI Processor Market - 2024-2031

出版日期: 2024年08月06日 | 出版商:

DataM Intelligence | 英文 213 Pages | 商品交期: 最快1-2个工作天内

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简介目录

概述

全球边缘人工智慧处理器市场将于 2023 年达到 22 亿美元，预计到 2031 年将达到 83 亿美元，2024-2031 年预测期间复合年增长率为 18.6%。

能源效率在边缘运算环境中至关重要，特别是对于电池供电设备和物联网感测器而言。边缘人工智慧处理器製造商越来越注重开发节能架构和低功耗设计，以延长电池寿命并降低营运成本。节能边缘人工智慧处理器可延长设备运行时间，并支援边缘运算解决方案的可持续部署。

例如，2024 年 1 月 12 日，e-con Systems 和领先的人工智慧半导体公司 Ambarella, Inc. 宣布建立合作伙伴关係，推出他们的合作企业：e-con 机器人计算平台 (eRCP)。它是围绕着 Ambarella 的顶级 CV72S 边缘人工智慧系统单晶片 (SoC) 设计的，这个创新平台专门满足机器人领域的需求。在快速发展的机器人领域，快速原型设计和卓越的性能都是重要的支柱。 Ambarella 的使用者友善 Cooper 开发者平台提供视觉功能和每瓦人工智慧效能。

由于增强隐私和安全性的需求，北美各行业对边缘运算设备的需求正在增长。组织正在部署边缘人工智慧处理器以实现边缘运算功能，支援智慧城市、工业物联网和医疗保健等用例。这些因素推动了人工智慧技术的创新，推动了针对北美市场量身定制的先进边缘人工智慧处理器架构、演算法和应用程式的开发。

动力学

将消费者转向边缘运算

边缘运算环境通常需要具有高运算能力和效率的AI处理器来即时处理资料并满足效能需求。因此，人们不断推动人工智慧处理器技术的进步，以提供更高的效能和效率，刺激市场竞争和创新，并推动全球边缘人工智慧处理器市场的发展。

将人工智慧处理器整合到边缘设备和系统中，为市场生态系统内的协作和伙伴关係开闢了新的机会。人工智慧处理器製造商与物联网设备製造商、软体开发商和系统整合商合作，提供满足边缘运算应用特定要求的整合解决方案，从而扩大其市场份额和收入潜力。

例如，2024年1月11日，以其创新技术解决方案而闻名的广达电脑公司与领先的人工智慧半导体公司安霸公司在CES期间宣布扩大策略联盟。这种增强的合作现在包括利用安霸的 CV3-AD、CV7 和新的 N1 系列人工智慧系统单晶片 (SoC) 开发产品，代表着尖端人工智慧应用能力的显着飞跃。这些进步满足了市场对各种神经网路和大型语言模型（参数范围从数百万到数十亿）不断增长的需求。

不断成长的物联网产品需求

物联网设备产生了对边缘运算能力的需求，以处理这些设备产生的资料。对边缘人工智慧处理器的需求增加扩大了机会，推动市场成长。物联网设备会产生大量资料，通常需要在边缘进行即时处理和智慧决策，以提取见解并采取及时行动，从而推动市场需求和采用。

边缘人工智慧处理器透过将人工智慧推理从集中式伺服器卸载到边缘并节省频宽来优化物联网设备的效能。这种最佳化提高了物联网部署的效率，使边缘人工智慧处理器成为物联网生态系统中不可或缺的元件，并推动市场成长。物联网应用的多样性需要可以客製化并整合到各种物联网设备和系统中的人工智慧处理器。

该公司正在开发满足物联网设备要求的灵活边缘人工智慧处理器解决方案，推动全球边缘人工智慧处理器市场的发展。例如，2022 年 9 月 20 日，NVIDIA 推出了专为高精度边缘 AI 量身定制的突破性 NVIDIA IGX 平台，彻底改变了製造、物流和医疗保健等关键领域的安全保障。

这些行业依赖昂贵的客製化解决方案来完成特定任务，但 IGX 平台提供简单的可程式性来适应不同的要求。 IGX 是安全自主系统的基石，增强了人与机器之间的协作。在製造和物流领域，IGX 确保在工厂和仓库等严格监管的实体环境中增加一层安全性。

开发成本高

边缘人工智慧处理器技术的研发所需的大量前期投资可能会成为新市场参与者进入的障碍。高开发成本阻碍小公司进入市场，限制竞争并减少市场多样性。由于价格敏感，製造商不愿意采用边缘人工智慧处理器。这可能会阻碍边缘人工智慧产品的采用。

透过开发先进边缘人工智慧处理器解决方案所涉及的测试程序，可以大大延长上市时间。由于开发时间延长而导致边缘人工智慧处理器商业化的延迟，损害了市场成长。为了收回巨额的开发成本，边缘人工智慧处理器供应商必须为其产品收取溢价，这降低了他们在价格至关重要的市场中的竞争力。除了限制市场接受度之外，较高的产品价格还会吓跑潜在买家，并减缓整个市场的成长和采用。

Energy efficiency is critical in edge computing environments, especially for battery-powered devices and IoT sensors. Edge AI processor manufacturers increasingly focus on developing energy-efficient architectures and low-power consumption designs to prolong battery life and reduce operational costs. Energy-efficient edge AI processors enable longer device runtime and support sustainable deployment of edge computing solutions.

For instance, on January 12, 2024, e-con Systems and Ambarella, Inc., a leading-edge AI semiconductor company, announced a partnership unveiling their collaborative venture: the e-con Robotics Computing Platform (eRCP). It is engineered around Ambarella's top-tier CV72S edge AI system on chip (SoC), this innovative platform caters specifically to the needs of the robotics sector. In the rapidly evolving landscape of robotics, both rapid prototyping and superior performance stand as essential pillars. Ambarella's user-friendly Cooper Developer Platform delivers vision capabilities and AI performance per watt.

North America is experiencing a demand for edge computing devices across various industries, driven by the need for enhanced privacy and security. Organizations are deploying edge AI processors to enable edge computing capabilities, supporting use cases including smart cities, industrial IoT, and healthcare. These factors fuel innovation in AI technologies, driving the development of advanced edge AI processor architectures, algorithms, and applications tailored for North American markets.

Dynamics

Shifting Consumers to Edge Computing

Edge computing environments often require AI processors with high computational power and efficiency to process data in real time and meet performance demands. Consequently, there is a continuous push for advancements in AI processor technology to deliver higher performance and efficiency, stimulating market competition and innovation, and driving the global edge AI processor market.

Integrating AI processors into edge devices and systems opens up new opportunities for collaboration and partnerships within the market ecosystem. AI processor manufacturers collaborate with IoT device manufacturers, software developers, and system integrators to deliver integrated solutions that address the specific requirements of edge computing applications, thereby expanding their market presence and revenue potential.

For instance, on January 11, 2024, Quanta Computer Inc., renowned for its innovative technology solutions, and Ambarella, Inc., a leading-edge AI semiconductor firm, announced an expansion of their strategic alliance during CES. This enhanced collaboration now encompasses the development of products utilizing Ambarella's CV3-AD, CV7, and new N1 series AI systems-on-chip (SoCs), representing a notable leap in capabilities for cutting-edge AI applications. These advancements cater to the escalating market need for a wide spectrum of neural networks and large language models, ranging from millions to billions of parameters.

Increasing IoT Products Demand

IoT devices create a demand for edge computing capabilities to process data generated by these devices. This increased demand for edge AI processors expands the opportunities, driving market growth. IoT devices generate wide amounts of data that often require real-time processing and intelligent decision-making at the edge to extract insights and enable timely actions, thereby driving market demand and adoption.

Edge AI processors optimize the performance of IoT devices by offloading AI inference from centralized servers to the edge and conserving bandwidth. This optimization enhances the effectiveness of IoT deployments, making edge AI processors indispensable components in the IoT ecosystem and driving market growth. The diverse nature of IoT applications requires AI processors that can be customized and integrated into various IoT devices and systems.

Companies are developing flexible edge AI processor solutions that meet the requirements of IoT devices, driving the global edge AI processor market. For instance, on September 20, 2022, NVIDIA launched the groundbreaking NVIDIA IGX platform tailored for high-precision edge AI, revolutionizing security and safety in critical sectors like manufacturing, logistics, and healthcare.

These industries relied on expensive, custom-built solutions for specific tasks, but the IGX platform offers easy programmability to adapt to diverse requirements. It is serving as a cornerstone for secure autonomous systems, IGX enhances collaboration between humans and machines. In manufacturing and logistics, IGX ensures an added layer of safety in tightly regulated physical environments like factories and warehouses.

High Development Costs

The significant upfront investment required for research and development in edge AI processor technology can act as a barrier to entry for new market players. High development costs deter smaller companies from entering the market, limiting competition and reducing market diversity. Manufacturers are reluctant to adopt edge AI processors in price-sensitive. This can hinder the adoption of edge AI products.

The time-to-market can be greatly extended by the testing procedures involved in developing advanced edge AI processor solutions. Delays in the commercial availability of edge AI processors due to extended development timelines harm market growth. To recover the significant development costs, edge AI processor suppliers must charge a premium for their products, which reduces their ability to compete in markets where prices are crucial. In addition to limiting market acceptability, higher product prices can turn off potential buyers and slow down the growth and adoption of the market as a whole.

Segment Analysis

The global edge AI processor market is segmented based on type, device type, end-user, and region.

Growing Demand and Adoption in Consumer Devices

The consumer devices segment holds the largest share of the global edge AI processor. The adoption of smartphones is leading to a demand for edge AI processors in these consumer devices. The growing popularity of smart home devices fuels the demand for edge AI processors. These devices leverage edge AI for tasks enabling intelligent automation in the home environment.

Wearable devices incorporate edge AI processors to enable features like activity tracking, health monitoring, gesture recognition, and real-time notifications. The increasing adoption of wearable technology across consumer demographics contributes to the growth of edge AI processor demand in this segment. Entertainment platforms integrate edge AI processors to deliver interactive content recommendations and real-time content processing. Manufacturers are developing new products enhancing user boosts the adoption of edge AI in consumer devices.

For instance, on September 21, 2023, Lenovo launched its edge artificial intelligence (AI) services and solutions. With the introduction of "Lenovo TruScale for Edge and AI," Lenovo extends the proven cost advantages of its TruScale model to the widest and most inclusive edge portfolio available. This offering enables customers to leverage the company's cutting-edge services and solutions through a convenient pay-as-you-go model, facilitating SWT deployment of edge computing and the acquisition of AI-driven insights directly at the point of data generation.

Geographical Penetration

Growing Adoption of Advanced Technologies and Investment in North America

North America dominates the global edge AI processor market. Companies have a track record of innovation and market in edge computing and AI, positioning them as dominant in the global market. North America's significant investment in AI, fuels development efforts in edge AI processor technology. Major players are innovating edge AI solutions, contributing to the region's market dominance.

For instance, on January 10, 2024, Ambarella, Inc., a pioneering edge AI semiconductor company, introduced the cutting-edge Cooper Developer Platform. Cooper revolutionizes the integration of software, hardware, advanced AI models, and services, offering comprehensive support across Ambarella's entire AI systems-on-chip (SoCs) lineup. This platform streamlines the development process for customers through its flexible, modular, and prepackaged suite of hardware and software tools. It includes Cooper Metal, encompassing AI SoCs and board-level hardware solutions, and Cooper Foundry, a multi-layer software stack featuring Cooper Core, Cooper Foundation, Cooper Vision, and Cooper UX.

COVID-19 Impact Analysis

The COVID disrupted supply chains, production, and distribution of semiconductor component edge AI processors. International trade restrictions led to supply chain disruptions, affecting the availability of edge AI processors in the market. The COVID shifted demand patterns as consumers adapted to online learning, telemedicine, and e-commerce. The COVID accelerated digital transformation initiatives across industries, leading to increased investments in edge computing and AI technologies.

The pandemic boosted the use of remote monitoring and telehealth to support virtual healthcare delivery. Real-time medical data analysis at the edge was made possible in large part by edge AI processors, enabling uses in healthcare settings such as predictive analytics, diagnostic imaging, and remote patient monitoring and impacting the global edge processor market positively.

Russia and Ukraine War Impact Analysis

The conflict led to supply chain disruptions, and semiconductors essential for edge AI processor manufacturing. Ukraine is a raw materials exporter used in semiconductor production, and any disruptions to its supply chain could affect global semiconductor manufacturing, causing delays in production and affecting the availability of edge AI processors in the market. Uncertainties surrounding the Russia-Ukraine war created instability in global markets.

The conflict-affected markets in the regions are Eastern Europe and neighboring countries. Companies operating in these regions have faced challenges related to supply chain disruptions, increased costs, and political instability, impacting their ability to compete in the global edge AI processor market. Additionally, shifts in regional geopolitical dynamics could have influenced market dynamics and trade relationships, potentially reshaping market structures and competitive landscapes.

By Type

Central Processing Unit (CPU)
Graphics Processing Unit (GPU)
Application Specific Integrated Circuit (ASIC)

By Device Type

Consumer Devices
Enterprise Devices

By End-User

Automotive and Transportation
Healthcare
Consumer Electronics
Retail and E-commerce
Others

By Region

North America
- U.S.
- Canada
- Mexico
Europe
- Germany
- UK
- France
- Italy
- Russia
- Rest of Europe
South America
- Brazil
- Argentina
- Rest of South America
Asia-Pacic
- China
- India
- Japan
- Australia
- Rest of Asia-Pacic
Middle East and Africa

Key Developments

On January 8, 2024, Intel announced the era of AI-powered computing with the introduction of its new lineup of processors for mobile, desktop, and edge devices at CES 2024. The highlight of Intel's announcement is the unveiling of the Intel Core 14th Gen processor family, alongside the introduction of Intel Core Ultra-powered systems. This initiative underscores Intel's dedication to addressing a wide range of user requirements and propelling advancements in computing standards.
On February 27, 2024, Intel launched its AI PC processors and platforms at MWC 2024, including a preview of the new Xeon processors and edge platform. Among the highlights is the Granite Rapids-D Xeon processor, boasting integrated AI acceleration and the latest P-core generation, set to hit the market in 2025.
On June 15, 2023, STMicroelectronics introduced an advanced line of 64-bit microprocessors tailored for edge computing, offering upgraded performance, and specialized functionalities crucial for real-time processing of data-heavy machine learning algorithms prevalent in industrial sectors. It is leading the pack in the STM32MP25 microprocessor, equipped with a dedicated neural processing unit engineered to bolster edge AI endeavors.

Competitive Landscape

The major global players in the edge AI processor market include Apple, Inc., Samsung Electronics Co., Ltd., Mythic, Qualcomm Technologies, Inc., Huawei Technologies Co., Ltd., Intel Corporation, Google LLC, NVIDIA Corporation, Arm Limited, and Advanced Micro Devices, Inc.

Why Purchase the Report?

To visualize the global edge AI processor market segmentation based on type, device type, end-user, and region, as well as understand critical commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous edge AI processor market-level data points with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of critical products of all the major players.

The global edge AI processor market report would provide approximately 62 tables, 53 figures, and 213 Pages.

Target Audience 2023

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Type
3.2. Snippet by Device Type
3.3. Snippet by End-User
3.4. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Shifting Consumers to Edge Computing
  - 4.1.1.2. Increasing IoT Products Demand
- 4.1.2. Restraints
  - 4.1.2.1. High Development Costs
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion

7. By Type

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 7.1.2. Market Attractiveness Index, By Type
7.2. Central Processing Unit (CPU)*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Graphics Processing Unit (GPU)
7.4. Application Specific Integrated Circuit (ASIC)

8. By Device Type

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 8.1.2. Market Attractiveness Index, By Device Type
8.2. Consumer Devices*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Enterprise Devices

9. By End-User

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 9.1.2. Market Attractiveness Index, By End-User
9.2. Automotive and Transportation*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. Healthcare
9.4. Consumer Electronics
9.5. Retail and E-commerce
9.6. Others

10. By Region

10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 10.1.2. Market Attractiveness Index, By Region
10.2. North America
- 10.2.1. Introduction
- 10.2.2. Key Region-Specific Dynamics
- 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.2.6.1. U.S.
  - 10.2.6.2. Canada
  - 10.2.6.3. Mexico
10.3. Europe
- 10.3.1. Introduction
- 10.3.2. Key Region-Specific Dynamics
- 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.3.6.1. Germany
  - 10.3.6.2. UK
  - 10.3.6.3. France
  - 10.3.6.4. Italy
  - 10.3.6.5. Russia
  - 10.3.6.6. Rest of Europe
10.4. South America
- 10.4.1. Introduction
- 10.4.2. Key Region-Specific Dynamics
- 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.4.6.1. Brazil
  - 10.4.6.2. Argentina
  - 10.4.6.3. Rest of South America
10.5. Asia-Pacic
- 10.5.1. Introduction
- 10.5.2. Key Region-Specific Dynamics
- 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.5.6.1. China
  - 10.5.6.2. India
  - 10.5.6.3. Japan
  - 10.5.6.4. Australia
  - 10.5.6.5. Rest of Asia-Pacic
10.6. Middle East and Africa
- 10.6.1. Introduction
- 10.6.2. Key Region-Specific Dynamics
- 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Device Type
- 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

11. Competitive Landscape

11.1. Competitive Scenario
11.2. Market Positioning/Share Analysis
11.3. Mergers and Acquisitions Analysis

12. Company Profiles

12.1. Apple, Inc.*
- 12.1.1. Company Overview
- 12.1.2. Product Portfolio and Description
- 12.1.3. Financial Overview
- 12.1.4. Key Developments
12.2. Samsung Electronics Co., Ltd.
12.3. Mythic
12.4. Qualcomm Technologies, Inc.
12.5. Huawei Technologies Co., Ltd.
12.6. Intel Corporation
12.7. Google LLC
12.8. NVIDIA Corporation
12.9. Arm Limited
12.10. Advanced Micro Devices, Inc.

LIST NOT EXHAUSTIVE