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IoT 人工智能邊緣運算

市場調查報告書

商品編碼

1529362

全球邊緣人工智慧處理器市場 - 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個工作天內

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簡介目錄

概述

全球邊緣人工智慧處理器市場將於 2023 年達到 22 億美元，預計到 2031 年將達到 83 億美元，2024-2031 年預測期間複合年成長率為 18.6%。

能源效率在邊緣運算環境中至關重要，特別是對於電池供電設備和物聯網感測器而言。邊緣人工智慧處理器製造商越來越注重開發節能架構和低功耗設計，以延長電池壽命並降低營運成本。節能邊緣人工智慧處理器可延長設備運行時間，並支援邊緣運算解決方案的永續部署。

例如，2024 年 1 月 12 日，e-con Systems 和領先的人工智慧半導體公司 Ambarella, Inc. 宣佈建立合作夥伴關係，推出他們的合作企業：e-con 機器人計算平台 (eRCP)。它是圍繞著 Ambarella 的頂級 CV72S 邊緣人工智慧系統單晶片 (SoC) 設計的，這個創新平台專門滿足機器人領域的需求。在快速發展的機器人領域，快速原型設計和卓越的性能都是重要的支柱。 Ambarella 的使用者友善 Cooper 開發者平台提供視覺功能和每瓦人工智慧效能。

由於增強隱私和安全性的需求，北美各行業對邊緣運算設備的需求正在成長。組織正在部署邊緣人工智慧處理器以實現邊緣運算功能，支援智慧城市、工業物聯網和醫療保健等用例。這些因素推動了人工智慧技術的創新，推動了針對北美市場量身定做的先進邊緣人工智慧處理器架構、演算法和應用程式的開發。

動力學

將消費者轉向邊緣運算

邊緣運算環境通常需要具有高運算能力和效率的AI處理器來即時處理資料並滿足效能需求。因此，人們不斷推動人工智慧處理器技術的進步，以提供更高的效能和效率，刺激市場競爭和創新，並推動全球邊緣人工智慧處理器市場的發展。

將人工智慧處理器整合到邊緣設備和系統中，為市場生態系統內的協作和夥伴關係開闢了新的機會。人工智慧處理器製造商與物聯網設備製造商、軟體開發商和系統整合商合作，提供滿足邊緣運算應用特定要求的整合解決方案，從而擴大其市場佔有率和收入潛力。

例如，2024年1月11日，以其創新技術解決方案而聞名的廣達電腦公司與領先的人工智慧半導體公司安霸公司在CES期間宣布擴大策略聯盟。這種增強的合作現在包括利用安霸的 CV3-AD、CV7 和新的 N1 系列人工智慧系統單晶片 (SoC) 開發產品，代表著尖端人工智慧應用能力的顯著飛躍。這些進步滿足了市場對各種神經網路和大型語言模型（參數範圍從數百萬到數十億）不斷成長的需求。

不斷成長的物聯網產品需求

物聯網設備產生了對邊緣運算能力的需求，以處理這些設備產生的資料。對邊緣人工智慧處理器的需求增加擴大了機會，推動市場成長。物聯網設備會產生大量資料，通常需要在邊緣進行即時處理和智慧決策，以提取見解並採取及時行動，從而推動市場需求和採用。

邊緣人工智慧處理器透過將人工智慧推理從集中式伺服器卸載到邊緣並節省頻寬來最佳化物聯網設備的效能。這種最佳化提高了物聯網部署的效率，使邊緣人工智慧處理器成為物聯網生態系統中不可或缺的元件，並推動市場成長。物聯網應用的多樣性需要可以客製化並整合到各種物聯網設備和系統中的人工智慧處理器。

該公司正在開發滿足物聯網設備要求的靈活邊緣人工智慧處理器解決方案，推動全球邊緣人工智慧處理器市場的發展。例如，2022 年 9 月 20 日，NVIDIA 推出了專為高精度邊緣 AI 量身定做的突破性 NVIDIA IGX 平台，徹底改變了製造、物流和醫療保健等關鍵領域的安全保障。

這些行業依賴昂貴的客製化解決方案來完成特定任務，但 IGX 平台提供簡單的可程式性來適應不同的要求。 IGX 是安全自主系統的基石，增強了人與機器之間的協作。在製造和物流領域，IGX 確保在工廠和倉庫等嚴格監管的實體環境中增加一層安全性。

開發成本高

邊緣人工智慧處理器技術的研發所需的大量前期投資可能會成為新市場參與者進入的障礙。高開發成本阻礙小公司進入市場，限制競爭並減少市場多樣性。由於價格敏感，製造商不願意採用邊緣人工智慧處理器。這可能會阻礙邊緣人工智慧產品的採用。

透過開發先進邊緣人工智慧處理器解決方案所涉及的測試程序，可以大大延長上市時間。由於開發時間延長而導致邊緣人工智慧處理器商業化的延遲，損害了市場成長。為了收回巨額的開發成本，邊緣人工智慧處理器供應商必須為其產品收取溢價，這降低了他們在價格至關重要的市場中的競爭力。除了限制市場接受度之外，較高的產品價格還會嚇跑潛在買家，並減緩整個市場的成長和採用。

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