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1833599

2032 年人工智慧最佳化晶片市場預測：按晶片類型、處理類型、技術、應用、最終用戶和地區進行的全球分析

Artificial Intelligence Optimized Chips Market Forecasts to 2032 - Global Analysis By Chip Type (GPU, ASIC, FPGA, and Other Chip Types), Processing Type, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧最佳化晶片市場預計在 2025 年達到 948 億美元，到 2032 年將達到 5,759 億美元，預測期內的複合年成長率為 29.4%。

人工智慧最佳化晶片專注於先進的半導體解決方案，專為加速深度學習、自然語言處理和電腦視覺等人工智慧工作負載而設計。與通用處理器不同，這些晶片整合了 GPU、TPU 和 NPU 等專用架構，以提高速度、效率和可擴展性。雲端運算、自動駕駛汽車、機器人、智慧型裝置等領域日益成長的需求正在推動這些晶片的快速普及。隨著各行各業對人工智慧的採用日益廣泛，市場正在見證重大創新和投資，使其成為全球數位轉型的關鍵推動力。

據半導體行業協會稱，受資料中心和邊緣運算需求的推動，到 2027 年，人工智慧晶片的需求預計將以每年 30% 的速度成長。

深度學習的進展

現代神經網路，尤其是大型語言模型和複雜的電腦視覺系統，需要強大的平行處理能力，而通用 CPU 無法有效率地提供這種能力。這使得對 GPU 和 TPU 等專用硬體的需求變得至關重要，這些硬體的架構旨在加速矩陣運算和訓練工作負載。因此，晶片製造商正在競相開發更強大、更有效率的處理器，以處理下一代 AI 模型的運算負載，從而刺激市場大幅成長。

開發成本高

研發階段需要對專業工程人才和先進設計軟體進行巨額投資。此外，為了提高性能和能源效率而縮小奈米製程節點，會倍增製造成本，新建製造廠的成本高達數十億美元。這些不斷上升的成本可能會將市場力量集中在少數資金雄厚的科技巨頭和老牌半導體公司手中，使規模較小的創新者和新興企業難以競爭，並抑制市場上技術解決方案的多樣性。

邊緣運算的興起

隨著物聯網設備、智慧攝影機和自動駕駛汽車等資料來源的爆炸性成長，人們越來越需要在本地而非遠端雲端資料中心處理這些資訊。這種轉變需要一種新型低功耗、高效的AI晶片，能夠直接在裝置上執行推理任務，從而降低延遲、節省頻寬並增強資料隱私。這一趨勢正在激發創新，並催生出一個充滿活力、快速成長的邊緣AI處理器細分市場，涵蓋從製造業到消費性電子的各個領域。

地緣政治緊張局勢

不斷升級的地緣政治衝突，尤其是美國之間的衝突，對全球人工智慧晶片供應鏈構成了重大威脅。這些緊張局勢表現為貿易限制、出口管制以及對先進半導體技術的關稅，可能擾亂關鍵零件和製造設備的流通。這種分散化導致了市場碎片化，迫使企業建立成本高昂的冗餘供應鏈，並為長期規劃帶來了不確定性。這種環境不僅阻礙了全球合作與創新，還可能導致全球市場相關人員的成本膨脹和產品開發進度延遲。

COVID-19的影響：

疫情最初透過工廠關閉和供應鏈瓶頸擾亂了人工智慧晶片市場，導致生產延遲和零件短缺。然而，它也成為數位轉型的強大催化劑。遠距辦公、電子商務的激增以及物流和醫療診斷領域對人工智慧主導解決方案的採用，增加了對運算能力的需求。這些雙重影響凸顯了人工智慧基礎設施的關鍵作用，最終加速了對雲端運算和資料中心的投資，並迅速催生了對先進高效能晶片的需求，以支援更加依賴數位化的全球經濟。

GPU（圖形處理單元）部分預計將成為預測期內最大的部分

預計在預測期內，GPU（圖形處理器）領域將佔據最大的市場佔有率。 GPU 最初設計用於渲染複雜的圖形，其大規模平行架構非常適合訓練深度學習模型所需的矩陣和向量運算。此外，其成熟的軟體生態系統（包括 CUDA 等平台）為開發人員提供了有效利用其強大功能的重要工具。這種平行處理能力，加上廣泛的開發人員支持，使 GPU 成為人工智慧研究和資料中心的預設選擇，並鞏固了其在市場上的主導地位。

邊緣處理領域預計將在預測期內實現最高複合年成長率

邊緣處理領域預計將在預測期內呈現最高成長率，這反映了產業向分散式智慧的決定性轉變。隨著連網物聯網設備數量的快速成長，在邊緣本地處理資料對於最大限度地降低延遲、節省頻寬並確保即時應用的運作可靠性至關重要。這需要新一代人工智慧晶片，它不僅功能強大，而且節能高效、結構緊湊。因此，創新的重點是開發專門用於從自動駕駛汽車到智慧家電等各種應用的處理器，從而推動該領域的爆炸式成長。

佔比最大的地區：

預計北美將在預測期內佔據最大的市場佔有率。該地區匯聚了NVIDIA、英特爾和AMD等全球領先的科技巨頭，以及Google和微軟等超大規模資料中心業者，後者是AI晶片技術的主要消費者和創新者。此外，大量的創業投資資金籌措、政府對AI研究的大力支持以及金融、醫療保健和雲端運算等關鍵領域對AI的早期廣泛應用，共同打造了一個強大而成熟的生態系統，使其有望主導全球市場。

複合年成長率最高的地區：

預計亞太地區在預測期內的複合年成長率最高。這項成長主要得益於中國、日本和韓國等國家政府主導的大規模舉措旨在大力推動國內半導體製造和人工智慧發展。此外，龐大的電子製造基地、快速數位化的工業部門以及產生大量資料集的龐大人口，為人工智慧的應用提供了肥沃的土壤。這些動態，加上本土科技巨頭不斷增加的投資，使亞太地區成為成長最快的市場。

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目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章全球人工智慧最佳化晶片市場（按晶片類型）

  • GPU（圖形處理單元）
  • ASIC（專用積體電路）
    • TPU（張量處理單元）
    • 其他客製化 ASIC
  • FPGA（現場可程式化閘陣列）
  • 帶有AI加速器的CPU（中央處理器）
  • NPU（神經處理單元）
  • 其他尖端類型

6. 全球人工智慧最佳化晶片市場（按處理類型）

  • 邊緣處理
  • 雲端處理

第7章全球人工智慧最佳化晶片市場（按技術）

  • 系統晶片(SoC)
  • 系統級封裝(SiP)
  • 多晶片模組（MCM）
  • 其他技術

第8章全球人工智慧最佳化晶片市場（按應用）

  • 自然語言處理（NLP）
  • 電腦視覺
  • 機器人流程自動化（RPA）
  • 網路安全
  • 自動駕駛汽車和ADAS
  • 其他應用

第9章全球人工智慧最佳化晶片市場（按最終用戶）

  • 醫療保健和生命科學
  • BFSI（銀行、金融服務和保險）
  • 汽車和運輸
  • 零售與電子商務
  • 資訊科技/通訊
  • 政府和國防
  • 製造業
  • 能源與公共產業
  • 媒體與娛樂
  • 其他最終用戶

第 10 章全球人工智慧最佳化晶片市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第 12 章：公司概況

  • NVIDIA
  • AMD
  • Intel
  • Qualcomm
  • Apple
  • Google（Alphabet）
  • Amazon（AWS）
  • Huawei
  • Samsung
  • MediaTek
  • Broadcom
  • Arm
  • Graphcore
  • Cerebras Systems
  • SambaNova Systems
  • Groq
  • Tenstorrent
  • Cambricon
Product Code: SMRC31432

According to Stratistics MRC, the Global Artificial Intelligence Optimized Chips Market is accounted for $94.8 billion in 2025 and is expected to reach $575.9 billion by 2032 growing at a CAGR of 29.4% during the forecast period. Artificial Intelligence Optimized Chips focuses on advanced semiconductor solutions specifically designed to accelerate AI workloads, including deep learning, natural language processing, and computer vision. Unlike general-purpose processors, these chips integrate specialized architectures such as GPUs, TPUs, and NPUs for enhanced speed, efficiency, and scalability. Growing demand across cloud computing, autonomous vehicles, robotics, and smart devices is driving rapid adoption. With increasing AI deployment across industries, the market is witnessing significant innovation and investments, making it a critical enabler of digital transformation globally.

According to the Semiconductor Industry Association, AI chip demand is expected to grow 30% annually through 2027, driven by data center and edge computing needs.

Market Dynamics:

Driver:

Advancements in Deep Learning

Modern neural networks, particularly large language models and complex computer vision systems, demand immense parallel processing power that general-purpose CPUs cannot efficiently provide. This has created a critical need for specialized hardware like GPUs and TPUs that are architecturally designed to accelerate matrix operations and training workloads. Consequently, chipmakers are in a continuous race to develop more powerful and efficient processors specifically to keep up with the computational hunger of next-generation AI models, thereby fueling significant market growth.

Restraint:

High Development Costs

The research and development phase requires immense investment in specialized engineering talent and sophisticated design software. Moreover, moving to smaller nanometer process nodes for enhanced performance and power efficiency exponentially increases fabrication costs, with new fabrication plants costing billions of dollars. These soaring expenses concentrate market power among a few well-capitalized tech giants and established semiconductor players, making it exceptionally difficult for smaller innovators and startups to compete and potentially stifling the diversity of technological solutions in the market.

Opportunity:

Edge Computing Expansion

As data generation explodes from sources like IoT devices, smart cameras, and autonomous vehicles, there is a growing need to process this information locally rather than in distant cloud data centers. This shift demands a new class of low-power, high-efficiency AI chips that can perform inference tasks directly on-device, reducing latency, saving bandwidth, and enhancing data privacy. This trend is driving innovation and creating a vibrant, fast-growing segment for specialized edge-AI processors across industries from manufacturing to consumer electronics.

Threat:

Geopolitical Tensions

Escalating geopolitical disputes, particularly between the US and China, pose a significant threat to the global AI chip supply chain. These tensions have materialized as trade restrictions, export controls on advanced semiconductor technology, and tariffs, which can disrupt the flow of essential components and manufacturing equipment. Such fragmentation forces the bifurcation of the market, compels companies to build costly duplicate supply chains, and creates uncertainty in long-term planning. This environment not only hampers global collaboration and innovation but also risks inflating costs and delaying product development timelines for market players worldwide.

Covid-19 Impact:

The pandemic initially disrupted the AI chip market through factory closures and supply chain bottlenecks, causing production delays and component shortages. However, it simultaneously acted as a powerful accelerator for digital transformation. The surge in remote work, e-commerce, and the adoption of AI-driven solutions for logistics and healthcare diagnostics intensified the demand for computational power. This dual effect underscored the critical role of AI infrastructure, ultimately accelerating cloud and data center investments and fast-tracking the need for advanced, efficient chips to support a more digitally dependent global economy.

The GPU (Graphics Processing Unit) segment is expected to be the largest during the forecast period

The GPU (Graphics Processing Unit) segment is expected to account for the largest market share during the forecast period. Originally designed for rendering complex graphics, the GPU's massively parallel architecture is exceptionally well-suited for the matrix and vector calculations fundamental to training deep learning models. Furthermore, its established, mature software ecosystem, including platforms like CUDA, provides developers with the essential tools to efficiently harness its power. This combination of parallel processing prowess and extensive developer support makes GPUs the default choice for AI research and data centers, securing their leading market position.

The edge processing segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the edge processing segment is predicted to witness the highest growth rate, reflecting the industry's decisive shift towards decentralized intelligence. As the number of connected IoT devices skyrockets, processing data locally at the edge becomes critical to minimize latency, conserve bandwidth, and ensure operational reliability for real-time applications. This demands a new generation of AI chips that are not just powerful, but also highly power-efficient and compact. Consequently, intense innovation is focused on creating specialized processors for applications ranging from autonomous vehicles to smart appliances, driving explosive growth in this segment.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. The region is home to the world's leading technology behemoths, such as NVIDIA, Intel, and AMD, and hyperscalers like Google and Microsoft, who are both major consumers and innovators of AI chip technology. Moreover, substantial venture capital funding, strong governmental support for AI research, and early, widespread adoption of AI across key sectors like finance, healthcare, and cloud computing create a robust and mature ecosystem that consolidates its dominant position in the global market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. his growth is primarily fueled by massive government-led initiatives in countries like China, Japan, and South Korea that aggressively promote domestic semiconductor manufacturing and AI development. Additionally, the presence of a massive electronics manufacturing base, a rapidly digitizing industrial sector, and an enormous population generating vast datasets provide a fertile ground for AI adoption. These dynamics, combined with rising investments from local tech giants, position Asia Pacific as the fastest-growing market.

Key players in the market

Some of the key players in Artificial Intelligence Optimized Chips Market include NVIDIA, AMD, Intel, Qualcomm, Apple, Google (Alphabet), Amazon (AWS), Huawei, Samsung, MediaTek, Broadcom, Arm, Graphcore, Cerebras Systems, SambaNova Systems, Groq, Tenstorrent, and Cambricon.

Key Developments:

In September 2025, NVIDIA and Intel announced a collaboration to develop AI infrastructure and personal computing products integrating NVIDIA RTX GPU chiplets with Intel x86 SoCs.

In September 2025, Qualcomm announced Snapdragon 8 Elite Gen 5 chip for smartphones in 2026, featuring in-house Oryon CPU, 3nm TSMC process, and enhanced AI agent capabilities for real-time personalized AI experiences.

In May 2025, AMD positioned itself as an AI powerhouse at Computex 2025 with new Radeon AI PRO R9700 workstation GPU for edge AI and Ryzen AI 300 series chips, claiming competitive AI performance including 15% lead over Apple's M4 Pro.

Chip Types Covered:

  • GPU (Graphics Processing Unit)
  • ASIC (Application-Specific Integrated Circuit)
  • FPGA (Field-Programmable Gate Array)
  • CPU (Central Processing Unit) with AI Accelerators
  • NPU (Neural Processing Unit)
  • Other Chip Types

Processing Types Covered:

  • Edge Processing
  • Cloud Processing

Technologies Covered:

  • System-on-Chip (SoC)
  • System-in-Package (SiP)
  • Multi-Chip Module (MCM)
  • Other Technologies

Applications Covered:

  • Natural Language Processing (NLP)
  • Computer Vision
  • Robotic Process Automation (RPA)
  • Network Security
  • Autonomous Vehicles & ADAS
  • Other Applications

End Users Covered:

  • Healthcare & Life Sciences
  • BFSI (Banking, Financial Services, and Insurance)
  • Automotive & Transportation
  • Retail & E-commerce
  • IT & Telecommunications
  • Government & Defense
  • Manufacturing
  • Energy & Utilities
  • Media & Entertainment
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence Optimized Chips Market, By Chip Type

  • 5.1 Introduction
  • 5.2 GPU (Graphics Processing Unit)
  • 5.3 ASIC (Application-Specific Integrated Circuit)
    • 5.3.1 TPU (Tensor Processing Unit)
    • 5.3.2 Other Custom ASICs
  • 5.4 FPGA (Field-Programmable Gate Array)
  • 5.5 CPU (Central Processing Unit) with AI Accelerators
  • 5.6 NPU (Neural Processing Unit)
  • 5.7 Other Chip Types

6 Global Artificial Intelligence Optimized Chips Market, By Processing Type

  • 6.1 Introduction
  • 6.2 Edge Processing
  • 6.3 Cloud Processing

7 Global Artificial Intelligence Optimized Chips Market, By Technology

  • 7.1 Introduction
  • 7.2 System-on-Chip (SoC)
  • 7.3 System-in-Package (SiP)
  • 7.4 Multi-Chip Module (MCM)
  • 7.5 Other Technologies

8 Global Artificial Intelligence Optimized Chips Market, By Application

  • 8.1 Introduction
  • 8.2 Natural Language Processing (NLP)
  • 8.3 Computer Vision
  • 8.4 Robotic Process Automation (RPA)
  • 8.5 Network Security
  • 8.6 Autonomous Vehicles & ADAS
  • 8.7 Other Applications

9 Global Artificial Intelligence Optimized Chips Market, By End User

  • 9.1 Introduction
  • 9.2 Healthcare & Life Sciences
  • 9.3 BFSI (Banking, Financial Services, and Insurance)
  • 9.4 Automotive & Transportation
  • 9.5 Retail & E-commerce
  • 9.6 IT & Telecommunications
  • 9.7 Government & Defense
  • 9.8 Manufacturing
  • 9.9 Energy & Utilities
  • 9.10 Media & Entertainment
  • 9.11 Other End Users

10 Global Artificial Intelligence Optimized Chips Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 NVIDIA
  • 12.2 AMD
  • 12.3 Intel
  • 12.4 Qualcomm
  • 12.5 Apple
  • 12.6 Google (Alphabet)
  • 12.7 Amazon (AWS)
  • 12.8 Huawei
  • 12.9 Samsung
  • 12.10 MediaTek
  • 12.11 Broadcom
  • 12.12 Arm
  • 12.13 Graphcore
  • 12.14 Cerebras Systems
  • 12.15 SambaNova Systems
  • 12.16 Groq
  • 12.17 Tenstorrent
  • 12.18 Cambricon

List of Tables

  • Table 1 Global Artificial Intelligence Optimized Chips Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Artificial Intelligence Optimized Chips Market Outlook, By Chip Type (2024-2032) ($MN)
  • Table 3 Global Artificial Intelligence Optimized Chips Market Outlook, By GPU (Graphics Processing Unit) (2024-2032) ($MN)
  • Table 4 Global Artificial Intelligence Optimized Chips Market Outlook, By ASIC (Application-Specific Integrated Circuit) (2024-2032) ($MN)
  • Table 5 Global Artificial Intelligence Optimized Chips Market Outlook, By TPU (Tensor Processing Unit) (2024-2032) ($MN)
  • Table 6 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Custom ASICs (2024-2032) ($MN)
  • Table 7 Global Artificial Intelligence Optimized Chips Market Outlook, By FPGA (Field-Programmable Gate Array) (2024-2032) ($MN)
  • Table 8 Global Artificial Intelligence Optimized Chips Market Outlook, By CPU (Central Processing Unit) with AI Accelerators (2024-2032) ($MN)
  • Table 9 Global Artificial Intelligence Optimized Chips Market Outlook, By NPU (Neural Processing Unit) (2024-2032) ($MN)
  • Table 10 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Chip Types (2024-2032) ($MN)
  • Table 11 Global Artificial Intelligence Optimized Chips Market Outlook, By Processing Type (2024-2032) ($MN)
  • Table 12 Global Artificial Intelligence Optimized Chips Market Outlook, By Edge Processing (2024-2032) ($MN)
  • Table 13 Global Artificial Intelligence Optimized Chips Market Outlook, By Cloud Processing (2024-2032) ($MN)
  • Table 14 Global Artificial Intelligence Optimized Chips Market Outlook, By Technology (2024-2032) ($MN)
  • Table 15 Global Artificial Intelligence Optimized Chips Market Outlook, By System-on-Chip (SoC) (2024-2032) ($MN)
  • Table 16 Global Artificial Intelligence Optimized Chips Market Outlook, By System-in-Package (SiP) (2024-2032) ($MN)
  • Table 17 Global Artificial Intelligence Optimized Chips Market Outlook, By Multi-Chip Module (MCM) (2024-2032) ($MN)
  • Table 18 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 19 Global Artificial Intelligence Optimized Chips Market Outlook, By Application (2024-2032) ($MN)
  • Table 20 Global Artificial Intelligence Optimized Chips Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 21 Global Artificial Intelligence Optimized Chips Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 22 Global Artificial Intelligence Optimized Chips Market Outlook, By Robotic Process Automation (RPA) (2024-2032) ($MN)
  • Table 23 Global Artificial Intelligence Optimized Chips Market Outlook, By Network Security (2024-2032) ($MN)
  • Table 24 Global Artificial Intelligence Optimized Chips Market Outlook, By Autonomous Vehicles & ADAS (2024-2032) ($MN)
  • Table 25 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 26 Global Artificial Intelligence Optimized Chips Market Outlook, By End User (2024-2032) ($MN)
  • Table 27 Global Artificial Intelligence Optimized Chips Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 28 Global Artificial Intelligence Optimized Chips Market Outlook, By BFSI (Banking, Financial Services, and Insurance) (2024-2032) ($MN)
  • Table 29 Global Artificial Intelligence Optimized Chips Market Outlook, By Automotive & Transportation (2024-2032) ($MN)
  • Table 30 Global Artificial Intelligence Optimized Chips Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 31 Global Artificial Intelligence Optimized Chips Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
  • Table 32 Global Artificial Intelligence Optimized Chips Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 33 Global Artificial Intelligence Optimized Chips Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 34 Global Artificial Intelligence Optimized Chips Market Outlook, By Energy & Utilities (2024-2032) ($MN)
  • Table 35 Global Artificial Intelligence Optimized Chips Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 36 Global Artificial Intelligence Optimized Chips Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.