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市場調查報告書
商品編碼
1518865

深度學習晶片組市場：2024-2032 年全球產業分析、規模、佔有率、成長、趨勢、預測

Deep Learning Chipset Market: Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2024-2032
出版日期: | 出版商: Persistence Market Research | 英文 250 Pages | 商品交期: 2-5個工作天內

價格
簡介目錄

Persistence Market Research最近發佈了一份關於全球深度學習晶片組市場的綜合報告。該報告全面評估了主要市場動態，包括驅動因素、趨勢、機會和課題，並提供了有關市場結構的詳細見解。

重要見解

  • 深度學習晶片組市場規模（2024年）：101億美元
  • 預計市值（2032年）：728億美元
  • 全球市場成長率（2024-2032年複合年增長率）：28.0%

深度學習晶片組市場 - 報告範圍：

深度學習晶片組是各種應用的重要組件，包括資料中心、自動駕駛汽車、醫療保健和消費性電子產品。這些晶片組支援人工智慧 (AI) 和機器學習 (ML) 任務所需的複雜運算，推動技術和創新的進步。深度學習晶片組市場服務於眾多行業，包括科技巨頭、汽車製造商、醫療保健提供者和消費性電子製造商。市場成長的驅動力包括人工智慧和機器學習的日益普及、大數據分析的激增以及提高運算能力和效率的晶片組技術的進步。

市場成長動力：

全球深度學習晶片組市場受到幾個關鍵因素的推動，例如各行業對人工智慧和機器學習應用的需求不斷增長。數位轉型工作產生的數據量不斷增加以及對即時數據處理的需求正在推動深度學習晶片組的採用。專用積體電路（ASIC）、圖形處理單元（GPU）和張量處理單元（TPU）的發展等技術進步帶來了性能、能源效率和可擴展性的提高，推動了市場的成長。此外，人工智慧研發投資的增加，加上基於雲端的服務和邊緣運算的擴展，正在為市場參與者創造新的途徑來接觸更廣泛的客戶群。

市場限制因素：

儘管成長前景廣闊，但深度學習晶片組市場面臨高開發成本、技術複雜性和監管合規性等課題。設計和製造先進晶片組需要大量投資，這對中小型企業造成了經濟障礙。此外，將深度學習晶片組整合到現有基礎設施並確保與各種人工智慧框架的兼容性相關的技術複雜性可能會阻礙市場滲透。對監管合規性和資料隱私的擔憂也帶來了課題，特別是在醫療保健和金融等對人工智慧和機器學習技術的使用有嚴格監管的行業。

市場機會：

由於技術創新、新應用和不斷發展的商業模式，深度學習晶片組市場提供了巨大的成長機會。將人工智慧和機器學習融入自動駕駛汽車、機器人和智慧城市等新興領域將擴大市場範圍並刺激創新。策略合作夥伴關係、合併和收購使公司能夠利用互補技術並擴大其產品組合。研發投資，加上經濟高效且節能的晶片組的推出，對於利用新機會並在動態深度學習領域保持市場領先地位至關重要。

本報告解決的關鍵問題

  • 推動深度學習晶片組市場全球成長的關鍵因素是什麼？
  • 哪些晶片組類型和應用正在推動深度學習在各行業的採用？
  • 技術進步如何改變深度學習晶片組市場的競爭格局？
  • 誰是深度學習晶片組市場的主要公司？ 他們採取什麼策略來維持市場地位？
  • 全球深度學習晶片市場的新趨勢和未來前景如何？

目錄

第1章 內容提要

第2章 市場概況

  • 市場範圍/分類
  • 市場定義/範圍/限制

第3章 市場背景

  • 市場動態
  • 情景預測
  • 機會圖分析
  • 產品生命週期分析
  • 供應鏈分析
  • 投資可行性矩陣
  • 價值鏈分析
  • PESTLE 與 Porter 分析
  • 監管狀況
  • 各地區母公司市場前景
  • 生產與消費統計
  • 進出口統計

第4章 全球深度學習晶片組市場分析

  • 過去的市場規模金額（十億美元）和數量（單位）分析，2019-2023
  • 2024-2032 年當前和未來市場規模價值（十億美元）和數量（單位）預測
    • 同比增長趨勢分析
    • 絕對量機會分析

第5章 全球深度學習晶片組市場分析：按類型

  • 簡介/主要發現
  • 2019-2023 年按類型劃分的歷史市場規模（十億美元）和交易量（單位）分析
  • 2024-2032 年當前和未來市場規模價值（十億美元）和數量（單位）（按類型）分析和預測
    • 中央處理器（CPU）
    • 圖形處理單元 (GPU)
    • 現場可編程門陣列 (FPGA)
    • 專用集成電路 (ASIC)
    • 其他（NPU和混合晶片）
  • 同比成長趨勢分析：依類型，2019-2023
  • 絕對機會分析：按類型，2024-2032

第6章 全球深度學習晶片組市場分析：依技術分類

  • 簡介/主要發現
  • 2019-2023 年按技術劃分的歷史市場規模價值（十億美元）和交易量（單位）分析
  • 2024-2032 年按技術劃分的當前和未來市場規模價值（十億美元）和數量（單位）分析和預測
    • 系統單晶片 (SOC)
    • 系統級封裝 (SIP)
    • 多芯片模塊
    • 其他
  • 年比成長趨勢分析：依技術分類，2019-2023
  • 絕對機會分析：依技術分類，2024-2032

第7章 全球深度學習晶片組市場分析：按地區

  • 介紹
  • 2019-2023 年按地區歷史市場規模（十億美元）及成交量（單位）分析
  • 2024-2032 年各地區當前市場規模價值（十億美元）與數量（單位）分析與預測
    • 北美
    • 拉丁美洲
    • 歐洲
    • 亞太地區
    • 中東/非洲
  • 市場吸引力分析：按地區

第8章 北美深度學習晶片組市場分析：按國家/地區

第9章 拉丁美洲深度學習晶片組市場分析：按國家/地區

第10章 歐洲深度學習晶片組市場分析：依國家分類

第11章 亞太地區深度學習晶片組市場分析：按國家/地區

第12章 中東和非洲深度學習晶片組市場分析：按國家/地區

第13章 主要國家深度學習晶片市場分析

  • 美國
  • 加拿大
  • 巴西
  • 墨西哥
  • 德國
  • 英國
  • 法國
  • 西班牙
  • 義大利
  • 中國
  • 日本
  • 韓國
  • 新加坡
  • 泰國
  • 印度尼西亞
  • 澳大利亞
  • 紐西蘭
  • 海灣合作委員會國家
  • 南非
  • 以色列

第14章 市場結構分析

  • 比賽儀表板
  • 競爭標桿
  • 主要參與者的市場佔有率分析

第15章 競爭分析

  • 競爭對手詳情
    • Alphabet Inc.
    • Amazon.Com, Inc.
    • Advanced Micro Devices, Inc.
    • Baidu, Inc.
    • Bitmain Technologies Ltd.
    • Intel Corporation
    • Nvidia Corporation
    • Qualcomm Incorporated
    • Samsung Electronics Co. Ltd.
    • Xilinx, Inc

第16章 使用的假設和首字母縮略詞

第17章 研究方法論

簡介目錄
Product Code: PMRREP33373

Persistence Market Research has recently released a comprehensive report on the worldwide market for deep learning chipsets. The report offers a thorough assessment of crucial market dynamics, including drivers, trends, opportunities, and challenges, providing detailed insights into the market structure.

Key Insights:

  • Deep Learning Chipset Market Size (2024E): USD 10.1 Billion
  • Projected Market Value (2032F): USD 72.8 Billion
  • Global Market Growth Rate (CAGR 2024 to 2032): 28.0%

Deep Learning Chipset Market - Report Scope:

Deep learning chipsets are integral components in various applications such as data centers, autonomous vehicles, healthcare, and consumer electronics. These chipsets enable complex computations required for artificial intelligence (AI) and machine learning (ML) tasks, driving advancements in technology and innovation. The deep learning chipset market caters to a broad range of industries, including technology giants, automotive manufacturers, healthcare providers, and consumer electronics companies. Market growth is driven by the increasing adoption of AI and ML, the surge in big data analytics, and advancements in chipset technology enhancing computational power and efficiency.

Market Growth Drivers:

The global deep learning chipset market is propelled by several key factors, including the rising demand for AI and ML applications across various industries. The growing volume of data generated by digital transformation initiatives and the need for real-time data processing drive the adoption of deep learning chipsets. Technological advancements, such as the development of application-specific integrated circuits (ASICs), graphics processing units (GPUs), and tensor processing units (TPUs), offer improved performance, energy efficiency, and scalability, fostering market growth. Moreover, the increasing investment in AI research and development, coupled with the expansion of cloud-based services and edge computing, creates new avenues for market players to reach a wider customer base.

Market Restraints:

Despite promising growth prospects, the deep learning chipset market faces challenges related to high development costs, technical complexities, and regulatory compliance. The substantial investment required for designing and manufacturing advanced chipsets poses financial barriers for small and medium-sized enterprises (SMEs). Additionally, the technical complexities associated with integrating deep learning chipsets into existing infrastructure and ensuring compatibility with various AI frameworks can hinder market penetration. Regulatory compliance and data privacy concerns also pose challenges, particularly in industries such as healthcare and finance, where stringent regulations govern the use of AI and ML technologies.

Market Opportunities:

The deep learning chipset market presents significant growth opportunities driven by technological innovations, emerging applications, and evolving business models. The integration of AI and ML into emerging fields such as autonomous vehicles, robotics, and smart cities enhances market scope and stimulates innovation. Strategic partnerships, mergers, and acquisitions enable companies to leverage complementary technologies and expand their product portfolios. Investment in research and development, coupled with the introduction of cost-effective, energy-efficient chipsets, is essential to capitalize on emerging opportunities and sustain market leadership in the dynamic deep learning landscape.

Key Questions Answered in the Report:

  • What are the primary factors driving the growth of the deep learning chipset market globally?
  • Which chipset types and applications are driving deep learning adoption across different industries?
  • How are technological advancements reshaping the competitive landscape of the deep learning chipset market?
  • Who are the key players contributing to the deep learning chipset market, and what strategies are they employing to maintain market relevance?
  • What are the emerging trends and future prospects in the global deep learning chipset market?

Competitive Intelligence and Business Strategy:

Leading players in the global deep learning chipset market, including NVIDIA Corporation, Intel Corporation, and Advanced Micro Devices, Inc., focus on innovation, product differentiation, and strategic partnerships to gain a competitive edge. These companies invest in R&D to develop advanced deep learning chipsets, including GPUs, TPUs, and ASICs, catering to diverse AI and ML applications. Collaborations with technology providers, academic institutions, and regulatory agencies facilitate market access and promote technology adoption. Moreover, emphasis on open-source frameworks, developer communities, and customer education fosters market growth and enhances user experience in the rapidly evolving deep learning landscape.

Key Companies Profiled:

  • Alphabet Inc.
  • Amazon.Com, Inc.
  • Advanced Micro Devices, Inc.
  • Baidu, Inc.
  • Bitmain Technologies Ltd.
  • Intel Corporation
  • Nvidia Corporation
  • Qualcomm Incorporated
  • Samsung Electronics Co. Ltd.
  • Xilinx, Inc.

Global Deep Learning Chipset Market Outlook by Category

By Type:

  • Central Processing Units (CPUs)
  • Graphics Processing Units (GPUs)
  • Field Programmable Gate Arrays (FPGAs)
  • Application-Specific Integrated Circuits (ASICs)
  • Others (NPU & Hybrid Chip)

By Technology:

  • System-on-chip (SOC)
  • System-in-package (SIP)
  • Multi-Chip Module

By Region:

  • North America
  • Latin America
  • Europe
  • Asia Pacific
  • Middle East and Africa

Table of Contents

1. Executive Summary

  • 1.1. Global Market Outlook
  • 1.2. Demand-side Trends
  • 1.3. Supply-side Trends
  • 1.4. Technology Roadmap Analysis
  • 1.5. Analysis and Recommendations

2. Market Overview

  • 2.1. Market Coverage / Taxonomy
  • 2.2. Market Definition / Scope / Limitations

3. Market Background

  • 3.1. Market Dynamics
    • 3.1.1. Drivers
    • 3.1.2. Restraints
    • 3.1.3. Opportunity
    • 3.1.4. Trends
  • 3.2. Scenario Forecast
    • 3.2.1. Demand in Optimistic Scenario
    • 3.2.2. Demand in Likely Scenario
    • 3.2.3. Demand in Conservative Scenario
  • 3.3. Opportunity Map Analysis
  • 3.4. Product Life Cycle Analysis
  • 3.5. Supply Chain Analysis
    • 3.5.1. Supply Side Participants and their Roles
      • 3.5.1.1. Producers
      • 3.5.1.2. Mid-Level Participants (Traders/ Agents/ Brokers)
      • 3.5.1.3. Wholesalers and Distributors
    • 3.5.2. Value Added and Value Created at Node in the Supply Chain
    • 3.5.3. List of Raw Material Suppliers
    • 3.5.4. List of Existing and Potential Buyer's
  • 3.6. Investment Feasibility Matrix
  • 3.7. Value Chain Analysis
    • 3.7.1. Profit Margin Analysis
    • 3.7.2. Wholesalers and Distributors
    • 3.7.3. Retailers
  • 3.8. PESTLE and Porter's Analysis
  • 3.9. Regulatory Landscape
    • 3.9.1. By Key Regions
    • 3.9.2. By Key Countries
  • 3.10. Regional Parent Market Outlook
  • 3.11. Production and Consumption Statistics
  • 3.12. Import and Export Statistics

4. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast, 2024-2032

  • 4.1. Historical Market Size Value (US$ billion) & Volume (Units) Analysis, 2019-2023
  • 4.2. Current and Future Market Size Value (US$ billion) & Volume (Units) Projections, 2024-2032
    • 4.2.1. Y-o-Y Growth Trend Analysis
    • 4.2.2. Absolute $ Opportunity Analysis

5. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Type

  • 5.1. Introduction / Key Findings
  • 5.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Type, 2019-2023
  • 5.3. Current and Future Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Type, 2024-2032
    • 5.3.1. Central Processing Units (CPUs)
    • 5.3.2. Graphics Processing Units (GPUs)
    • 5.3.3. Field Programmable Gate Arrays (FPGAs)
    • 5.3.4. Application-Specific Integrated Circuits (ASICs)
    • 5.3.5. Others (NPU & Hybrid Chip)
  • 5.4. Y-o-Y Growth Trend Analysis By Type, 2019-2023
  • 5.5. Absolute $ Opportunity Analysis By Type, 2024-2032

6. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Technology

  • 6.1. Introduction / Key Findings
  • 6.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Technology, 2019-2023
  • 6.3. Current and Future Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Technology, 2024-2032
    • 6.3.1. System-on-chip (SOC))
    • 6.3.2. System-in-package (SIP
    • 6.3.3. Multi-Chip Module
    • 6.3.4. Others
  • 6.4. Y-o-Y Growth Trend Analysis By Technology, 2019-2023
  • 6.5. Absolute $ Opportunity Analysis By Technology, 2024-2032

7. Global Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Region

  • 7.1. Introduction
  • 7.2. Historical Market Size Value (US$ billion) & Volume (Units) Analysis By Region, 2019-2023
  • 7.3. Current Market Size Value (US$ billion) & Volume (Units) Analysis and Forecast By Region, 2024-2032
    • 7.3.1. North America
    • 7.3.2. Latin America
    • 7.3.3. Europe
    • 7.3.4. Asia Pacific
    • 7.3.5. Middle East and Africa
  • 7.4. Market Attractiveness Analysis By Region

8. North America Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

  • 8.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
  • 8.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
    • 8.2.1. By Country
      • 8.2.1.1. USA
      • 8.2.1.2. Canada
    • 8.2.2. By Type
    • 8.2.3. By Technology
  • 8.3. Market Attractiveness Analysis
    • 8.3.1. By Country
    • 8.3.2. By Type
    • 8.3.3. By Technology
  • 8.4. Key Takeaways

9. Latin America Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

  • 9.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
  • 9.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
    • 9.2.1. By Country
      • 9.2.1.1. Brazil
      • 9.2.1.2. Mexico
      • 9.2.1.3. Rest of Latin America
    • 9.2.2. By Type
    • 9.2.3. By Technology
  • 9.3. Market Attractiveness Analysis
    • 9.3.1. By Country
    • 9.3.2. By Type
    • 9.3.3. By Technology
  • 9.4. Key Takeaways

10. Europe Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

  • 10.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
  • 10.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
    • 10.2.1. By Country
      • 10.2.1.1. Germany
      • 10.2.1.2. United Kingdom
      • 10.2.1.3. France
      • 10.2.1.4. Spain
      • 10.2.1.5. Italy
      • 10.2.1.6. Rest of Europe
    • 10.2.2. By Type
    • 10.2.3. By Technology
  • 10.3. Market Attractiveness Analysis
    • 10.3.1. By Country
    • 10.3.2. By Type
    • 10.3.3. By Technology
  • 10.4. Key Takeaways

11. Asia Pacific Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

  • 11.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
  • 11.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
    • 11.2.1. By Country
      • 11.2.1.1. China
      • 11.2.1.2. Japan
      • 11.2.1.3. South Korea
      • 11.2.1.4. Singapore
      • 11.2.1.5. Thailand
      • 11.2.1.6. Indonesia
      • 11.2.1.7. Australia
      • 11.2.1.8. New Zealand
      • 11.2.1.9. Rest of Asia Pacific
    • 11.2.2. By Type
    • 11.2.3. By Technology
  • 11.3. Market Attractiveness Analysis
    • 11.3.1. By Country
    • 11.3.2. By Type
    • 11.3.3. By Technology
  • 11.4. Key Takeaways

12. Middle East and Africa Deep Learning Chipset Market Analysis 2019-2023 and Forecast 2024-2032, By Country

  • 12.1. Historical Market Size Value (US$ billion) & Volume (Units) Trend Analysis By Market Taxonomy, 2019-2023
  • 12.2. Market Size Value (US$ billion) & Volume (Units) Forecast By Market Taxonomy, 2024-2032
    • 12.2.1. By Country
      • 12.2.1.1. Gulf Cooperation Council Countries
      • 12.2.1.2. South Africa
      • 12.2.1.3. Israel
      • 12.2.1.4. Rest of Middle East and Africa
    • 12.2.2. By Type
    • 12.2.3. By Technology
  • 12.3. Market Attractiveness Analysis
    • 12.3.1. By Country
    • 12.3.2. By Type
    • 12.3.3. By Technology
  • 12.4. Key Takeaways

13. Key Countries Deep Learning Chipset Market Analysis

  • 13.1. USA
    • 13.1.1. Pricing Analysis
    • 13.1.2. Market Share Analysis, 2024
      • 13.1.2.1. By Type
      • 13.1.2.2. By Technology
  • 13.2. Canada
    • 13.2.1. Pricing Analysis
    • 13.2.2. Market Share Analysis, 2024
      • 13.2.2.1. By Type
      • 13.2.2.2. By Technology
  • 13.3. Brazil
    • 13.3.1. Pricing Analysis
    • 13.3.2. Market Share Analysis, 2024
      • 13.3.2.1. By Type
      • 13.3.2.2. By Technology
  • 13.4. Mexico
    • 13.4.1. Pricing Analysis
    • 13.4.2. Market Share Analysis, 2024
      • 13.4.2.1. By Type
      • 13.4.2.2. By Technology
  • 13.5. Germany
    • 13.5.1. Pricing Analysis
    • 13.5.2. Market Share Analysis, 2024
      • 13.5.2.1. By Type
      • 13.5.2.2. By Technology
  • 13.6. United Kingdom
    • 13.6.1. Pricing Analysis
    • 13.6.2. Market Share Analysis, 2024
      • 13.6.2.1. By Type
      • 13.6.2.2. By Technology
  • 13.7. France
    • 13.7.1. Pricing Analysis
    • 13.7.2. Market Share Analysis, 2024
      • 13.7.2.1. By Type
      • 13.7.2.2. By Technology
  • 13.8. Spain
    • 13.8.1. Pricing Analysis
    • 13.8.2. Market Share Analysis, 2024
      • 13.8.2.1. By Type
      • 13.8.2.2. By Technology
  • 13.9. Italy
    • 13.9.1. Pricing Analysis
    • 13.9.2. Market Share Analysis, 2024
      • 13.9.2.1. By Type
      • 13.9.2.2. By Technology
  • 13.10. China
    • 13.10.1. Pricing Analysis
    • 13.10.2. Market Share Analysis, 2024
      • 13.10.2.1. By Type
      • 13.10.2.2. By Technology
  • 13.11. Japan
    • 13.11.1. Pricing Analysis
    • 13.11.2. Market Share Analysis, 2024
      • 13.11.2.1. By Type
      • 13.11.2.2. By Technology
  • 13.12. South Korea
    • 13.12.1. Pricing Analysis
    • 13.12.2. Market Share Analysis, 2024
      • 13.12.2.1. By Type
      • 13.12.2.2. By Technology
  • 13.13. Singapore
    • 13.13.1. Pricing Analysis
    • 13.13.2. Market Share Analysis, 2024
      • 13.13.2.1. By Type
      • 13.13.2.2. By Technology
  • 13.14. Thailand
    • 13.14.1. Pricing Analysis
    • 13.14.2. Market Share Analysis, 2024
      • 13.14.2.1. By Type
      • 13.14.2.2. By Technology
  • 13.15. Indonesia
    • 13.15.1. Pricing Analysis
    • 13.15.2. Market Share Analysis, 2024
      • 13.15.2.1. By Type
      • 13.15.2.2. By Technology
  • 13.16. Australia
    • 13.16.1. Pricing Analysis
    • 13.16.2. Market Share Analysis, 2024
      • 13.16.2.1. By Type
      • 13.16.2.2. By Technology
  • 13.17. New Zealand
    • 13.17.1. Pricing Analysis
    • 13.17.2. Market Share Analysis, 2024
      • 13.17.2.1. By Type
      • 13.17.2.2. By Technology
  • 13.18. Gulf Cooperation Council Countries
    • 13.18.1. Pricing Analysis
    • 13.18.2. Market Share Analysis, 2024
      • 13.18.2.1. By Type
      • 13.18.2.2. By Technology
  • 13.19. South Africa
    • 13.19.1. Pricing Analysis
    • 13.19.2. Market Share Analysis, 2024
      • 13.19.2.1. By Type
      • 13.19.2.2. By Technology
  • 13.20. Israel
    • 13.20.1. Pricing Analysis
    • 13.20.2. Market Share Analysis, 2024
      • 13.20.2.1. By Type
      • 13.20.2.2. By Technology

14. Market Structure Analysis

  • 14.1. Competition Dashboard
  • 14.2. Competition Benchmarking
  • 14.3. Market Share Analysis of Top Players
    • 14.3.1. By Regional
    • 14.3.2. By Type
    • 14.3.3. By Technology

15. Competition Analysis

  • 15.1. Competition Deep Dive
    • 15.1.1. Alphabet Inc.
      • 15.1.1.1. Overview
      • 15.1.1.2. Product Portfolio
      • 15.1.1.3. Profitability by Market Segments
      • 15.1.1.4. Sales Footprint
      • 15.1.1.5. Strategy Overview
        • 15.1.1.5.1. Marketing Strategy
        • 15.1.1.5.2. Product Strategy
        • 15.1.1.5.3. Channel Strategy
    • 15.1.2. Amazon.Com, Inc.
      • 15.1.2.1. Overview
      • 15.1.2.2. Product Portfolio
      • 15.1.2.3. Profitability by Market Segments
      • 15.1.2.4. Sales Footprint
      • 15.1.2.5. Strategy Overview
        • 15.1.2.5.1. Marketing Strategy
        • 15.1.2.5.2. Product Strategy
        • 15.1.2.5.3. Channel Strategy
    • 15.1.3. Advanced Micro Devices, Inc.
      • 15.1.3.1. Overview
      • 15.1.3.2. Product Portfolio
      • 15.1.3.3. Profitability by Market Segments
      • 15.1.3.4. Sales Footprint
      • 15.1.3.5. Strategy Overview
        • 15.1.3.5.1. Marketing Strategy
        • 15.1.3.5.2. Product Strategy
        • 15.1.3.5.3. Channel Strategy
    • 15.1.4. Baidu, Inc.
      • 15.1.4.1. Overview
      • 15.1.4.2. Product Portfolio
      • 15.1.4.3. Profitability by Market Segments
      • 15.1.4.4. Sales Footprint
      • 15.1.4.5. Strategy Overview
        • 15.1.4.5.1. Marketing Strategy
        • 15.1.4.5.2. Product Strategy
        • 15.1.4.5.3. Channel Strategy
    • 15.1.5. Bitmain Technologies Ltd.
      • 15.1.5.1. Overview
      • 15.1.5.2. Product Portfolio
      • 15.1.5.3. Profitability by Market Segments
      • 15.1.5.4. Sales Footprint
      • 15.1.5.5. Strategy Overview
        • 15.1.5.5.1. Marketing Strategy
        • 15.1.5.5.2. Product Strategy
        • 15.1.5.5.3. Channel Strategy
    • 15.1.6. Intel Corporation
      • 15.1.6.1. Overview
      • 15.1.6.2. Product Portfolio
      • 15.1.6.3. Profitability by Market Segments
      • 15.1.6.4. Sales Footprint
      • 15.1.6.5. Strategy Overview
        • 15.1.6.5.1. Marketing Strategy
        • 15.1.6.5.2. Product Strategy
        • 15.1.6.5.3. Channel Strategy
    • 15.1.7. Nvidia Corporation
      • 15.1.7.1. Overview
      • 15.1.7.2. Product Portfolio
      • 15.1.7.3. Profitability by Market Segments
      • 15.1.7.4. Sales Footprint
      • 15.1.7.5. Strategy Overview
        • 15.1.7.5.1. Marketing Strategy
        • 15.1.7.5.2. Product Strategy
        • 15.1.7.5.3. Channel Strategy
    • 15.1.8. Qualcomm Incorporated
      • 15.1.8.1. Overview
      • 15.1.8.2. Product Portfolio
      • 15.1.8.3. Profitability by Market Segments
      • 15.1.8.4. Sales Footprint
      • 15.1.8.5. Strategy Overview
        • 15.1.8.5.1. Marketing Strategy
        • 15.1.8.5.2. Product Strategy
        • 15.1.8.5.3. Channel Strategy
    • 15.1.9. Samsung Electronics Co. Ltd.
      • 15.1.9.1. Overview
      • 15.1.9.2. Product Portfolio
      • 15.1.9.3. Profitability by Market Segments
      • 15.1.9.4. Sales Footprint
      • 15.1.9.5. Strategy Overview
        • 15.1.9.5.1. Marketing Strategy
        • 15.1.9.5.2. Product Strategy
        • 15.1.9.5.3. Channel Strategy
    • 15.1.10. Xilinx, Inc
      • 15.1.10.1. Overview
      • 15.1.10.2. Product Portfolio
      • 15.1.10.3. Profitability by Market Segments
      • 15.1.10.4. Sales Footprint
      • 15.1.10.5. Strategy Overview
        • 15.1.10.5.1. Marketing Strategy
        • 15.1.10.5.2. Product Strategy
        • 15.1.10.5.3. Channel Strategy

16. Assumptions & Acronyms Used

17. Research Methodology