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市場調查報告書
商品編碼
1534224

全球深度學習晶片市場規模研究（按晶片類型、技術、垂直產業和 2022-2032 年區域預測）

Global Deep Learning Chip Market Size Study, by Chip Type, by Technology, by Industry Vertical, and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3個工作天內

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簡介目錄

2023 年全球深度學習晶片市場價值約為110.5 億美元，預計在2024 年至2032 年的預測期內將以35.27% 的複合年成長率強勁成長。的專用硬體，特別是深度學習演算法。這些晶片最佳化了神經網路中涉及的複雜運算，從而提高了效能和效率。主要功能包括平行處理能力、高記憶體頻寬和低功耗。該市場的主要參與者包括 NVIDIA、英特爾和谷歌，它們各自為自動駕駛汽車、醫學成像和自然語言處理等各種應用開發先進的晶片。對人工智慧驅動解決方案不斷成長的需求推動了深度學習晶片產業的快速成長。

全球深度學習晶片市場是由量子運算的出現和深度學習晶片在機器人領域的不斷部署所推動的。深度學習晶片在機器人技術中的日益整合增強了它們處理複雜資料和執行複雜任務的能力，從而推動了市場擴張。這些晶片使機器人能夠從資料中學習、適應新情況並隨著時間的推移提高性能，這使得它們在製造、醫療保健和自主系統等行業中發揮著至關重要的作用。這種雙重影響極大地推動了市場的成長軌跡。此外，能夠自我開發和自主控制的自主機器人數量不斷增加，帶來了巨大的成長機會。然而，該行業面臨技術專業人才短缺等挑戰。測試、錯誤修復和雲端實施等任務主要由深度學習晶片管理，但缺乏必要的專業知識。

全球深度學習晶片市場研究涵蓋的關鍵區域包括亞太地區、北美、歐洲、拉丁美洲和世界其他地區。預計到 2023 年，亞太地區的複合年成長率將達到最高，這表明深度學習技術在各種應用中的快速採用和整合。這一成長的推動因素包括人工智慧投資的增加、技術基礎設施的擴大以及醫療保健、汽車和金融等行業對高級分析的需求不斷成長。中國、印度、日本和澳洲等主要市場正在引領這一趨勢，利用深度學習來提高各自領域的創新和效率。

報告中包括的主要市場參與者有：

  • 字母公司
  • 高通公司
  • 賽靈思公司
  • 比特大陸科技有限公司
  • 超微半導體公司
  • 英特爾公司
  • 英偉達公司
  • 百度公司
  • 亞馬遜公司
  • 三星電子有限公司

市場的詳細細分和細分市場解釋如下：

目錄

第 1 章：全球深度學習晶片市場執行摘要

  • 全球深度學習晶片市場規模及預測（2022-2032）
  • 區域概要
  • 分部摘要
    • 按晶片類型
    • 依技術
    • 按行業分類
  • 主要趨勢
  • 經濟衰退的影響
  • 分析師推薦與結論

第 2 章：全球深度學習晶片市場定義與研究假設

  • 研究目的
  • 市場定義
  • 研究假設
    • 包容與排除
    • 限制
    • 供給側分析
      • 可用性
      • 基礎設施
      • 監管環境
      • 市場競爭
      • 經濟可行性（消費者的角度）
    • 需求面分析
      • 監理框架
      • 技術進步
      • 環境考慮
      • 消費者意識和接受度
  • 估算方法
  • 研究涵蓋的年份
  • 貨幣兌換率

第3章：全球深度學習晶片市場動態

  • 市場促進因素
    • 量子計算的出現
    • 增強機器人技術的實施
  • 市場挑戰
    • 缺乏熟練勞動力
  • 市場機會
    • 自主機器人的出現
    • 各行業的採用率不斷提高

第4章：全球深度學習晶片市場產業分析

  • 波特的五力模型
    • 供應商的議價能力
    • 買家的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭競爭
    • 波特五力模型的未來方法
    • 波特的 5 力影響分析
  • PESTEL分析
    • 政治的
    • 經濟
    • 社會的
    • 技術性
    • 環境的
    • 合法的
  • 頂級投資機會
  • 最佳制勝策略
  • 顛覆性趨勢
  • 產業專家視角
  • 分析師推薦與結論

第 5 章：全球深度學習晶片市場規模與預測：按晶片類型 - 2022-2032

  • 細分儀表板
  • 全球深度學習晶片市場：2022年&2032年晶片類型營收趨勢分析
    • 圖形處理器
    • 專用積體電路
    • FPGA
    • 中央處理器
    • 其他

第 6 章：全球深度學習晶片市場規模與預測：按技術分類 - 2022-2032

  • 細分儀表板
  • 全球深度學習晶片市場：2022年及2032年技術收入趨勢分析
    • 系統單晶片 (SoC)
    • 系統級封裝 (SIP)
    • 多晶片模組
    • 其他

第 7 章：全球深度學習晶片市場規模與預測：按行業垂直分類 - 2022-2032

  • 細分儀表板
  • 全球深度學習晶片市場：2022年及2032年產業垂直收入趨勢分析
    • 媒體與廣告
    • BFSI
    • 資訊科技與電信
    • 零售
    • 衛生保健
    • 汽車
    • 其他

第 8 章：全球深度學習晶片市場規模及預測：按地區 - 2022-2032

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 西班牙
    • 義大利
    • 歐洲其他地區
  • 亞太
    • 中國
    • 印度
    • 日本
    • 澳洲
    • 韓國
    • 亞太地區其他地區
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 南非
    • 中東和非洲其他地區

第 9 章：競爭情報

  • 重點企業SWOT分析
  • 頂級市場策略
  • 公司簡介
    • Alphabet Inc
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • Qualcomm Incorporated
    • Xilinx, Inc.
    • Bitmain Technologies Ltd.
    • Advanced Micro Devices, Inc.
    • Intel Corporation
    • NVIDIA Corporation
    • Baidu, Inc.
    • Amazon.com, Inc.
    • Samsung Electronics Co. Ltd.

第 10 章：研究過程

  • 研究過程
    • 資料探勘
    • 分析
    • 市場預測
    • 驗證
    • 出版
  • 研究屬性
簡介目錄

Global Deep Learning Chip Market was valued at approximately USD 11.05 billion in 2023 and is expected to grow at a robust CAGR of 35.27% over the forecast period from 2024 to 2032. Deep learning chips are specialized hardware designed to accelerate artificial intelligence (AI) tasks, particularly deep learning algorithms. These chips optimize complex computations involved in neural networks, enhancing performance and efficiency. Key features include parallel processing capabilities, high memory bandwidth, and low power consumption. Major players in this market include NVIDIA, Intel, and Google, each developing advanced chips for various applications like autonomous vehicles, medical imaging, and natural language processing. The increasing demand for AI-driven solutions fuels the rapid growth of the deep learning chip industry.

The Global Deep Learning Chip Market is driven by the advent of quantum computing and the increasing deployment of deep learning chips in robotics. the growing integration of deep learning chips in robotics enhances their ability to process complex data and perform sophisticated tasks, driving market expansion. These chips enable robots to learn from data, adapt to new situations, and improve performance over time, making them crucial in industries such as manufacturing, healthcare, and autonomous systems. This dual influence significantly boosts the market's growth trajectory. Moreover, rising number of autonomous robots, capable of self-development and autonomous control, presents significant growth opportunities. However, the industry faces challenges such as a shortage of skilled professionals. Tasks such as testing, bug fixing, and cloud implementation, primarily managed by deep learning chips, suffer from a lack of requisite expertise.

The key regions considered for the Global Deep Learning Chip Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, Asia-Pacific region is projected to exhibit the highest CAGR during the forecast period, indicating a rapid adoption and integration of deep learning technologies in various applications. This growth is driven by increasing investments in artificial intelligence, expanding technological infrastructure, and rising demand for advanced analytics in industries such as healthcare, automotive, and finance. Key markets such as China, India, Japan, and Australia are leading this trend, leveraging deep learning to enhance innovation and efficiency in their respective sectors.

Major market players include in report are:

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

The detailed segments and sub-segments of the market are explained below:

By Chip Type

  • GPU
  • ASIC
  • FPGA
  • CPU
  • Others

By Technology

  • System-on-chip (SoC)
  • System-in-package (SIP)
  • Multi-chip module
  • Others

By Industry Vertical

  • Media & Advertising
  • BFSI
  • IT & Telecom
  • Retail
  • Healthcare
  • Automotive
  • Others

By Region:

  • North America
  • U.S.
  • Canada
  • Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • ROE
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • RoAPAC
  • Latin America
  • Brazil
  • Mexico
  • RoLA
  • Middle East & Africa
  • Saudi Arabia
  • South Africa
  • RoMEA

Years considered for the study are as follows:

  • Historical year - 2022
  • Base year - 2023
  • Forecast period - 2024 to 2032

Key Takeaways:

  • Market Estimates & Forecast for 10 years from 2022 to 2032.
  • Annualized revenues and regional level analysis for each market segment.
  • Detailed analysis of geographical landscape with Country level analysis of major regions.
  • Competitive landscape with information on major players in the market.
  • Analysis of key business strategies and recommendations on future market approach.
  • Analysis of competitive structure of the market.
  • Demand side and supply side analysis of the market

Table of Contents

Chapter 1. Global Deep Learning Chip Market Executive Summary

  • 1.1. Global Deep Learning Chip Market Size & Forecast (2022-2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Chip Type
    • 1.3.2. By Technology
    • 1.3.3. By Industry Vertical
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Deep Learning Chip Market Definition and Research Assumptions

  • 2.1. Research Objective
  • 2.2. Market Definition
  • 2.3. Research Assumptions
    • 2.3.1. Inclusion & Exclusion
    • 2.3.2. Limitations
    • 2.3.3. Supply Side Analysis
      • 2.3.3.1. Availability
      • 2.3.3.2. Infrastructure
      • 2.3.3.3. Regulatory Environment
      • 2.3.3.4. Market Competition
      • 2.3.3.5. Economic Viability (Consumer's Perspective)
    • 2.3.4. Demand Side Analysis
      • 2.3.4.1. Regulatory frameworks
      • 2.3.4.2. Technological Advancements
      • 2.3.4.3. Environmental Considerations
      • 2.3.4.4. Consumer Awareness & Acceptance
  • 2.4. Estimation Methodology
  • 2.5. Years Considered for the Study
  • 2.6. Currency Conversion Rates

Chapter 3. Global Deep Learning Chip Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Emergence of Quantum Computing
    • 3.1.2. Enhanced Implementation in Robotics
  • 3.2. Market Challenges
    • 3.2.1. Dearth of Skilled Workforce
  • 3.3. Market Opportunities
    • 3.3.1. Emergence of Autonomous Robots
    • 3.3.2. Growing Adoption in Various Industries

Chapter 4. Global Deep Learning Chip Market Industry Analysis

  • 4.1. Porter's 5 Force Model
    • 4.1.1. Bargaining Power of Suppliers
    • 4.1.2. Bargaining Power of Buyers
    • 4.1.3. Threat of New Entrants
    • 4.1.4. Threat of Substitutes
    • 4.1.5. Competitive Rivalry
    • 4.1.6. Futuristic Approach to Porter's 5 Force Model
    • 4.1.7. Porter's 5 Force Impact Analysis
  • 4.2. PESTEL Analysis
    • 4.2.1. Political
    • 4.2.2. Economical
    • 4.2.3. Social
    • 4.2.4. Technological
    • 4.2.5. Environmental
    • 4.2.6. Legal
  • 4.3. Top investment opportunity
  • 4.4. Top winning strategies
  • 4.5. Disruptive Trends
  • 4.6. Industry Expert Perspective
  • 4.7. Analyst Recommendation & Conclusion

Chapter 5. Global Deep Learning Chip Market Size & Forecasts by Chip Type 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global Deep Learning Chip Market: Chip Type Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. GPU
    • 5.2.2. ASIC
    • 5.2.3. FPGA
    • 5.2.4. CPU
    • 5.2.5. Others

Chapter 6. Global Deep Learning Chip Market Size & Forecasts by Technology 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global Deep Learning Chip Market: Technology Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. System-on-chip (SoC)
    • 6.2.2. System-in-package (SIP)
    • 6.2.3. Multi-chip module
    • 6.2.4. Others

Chapter 7. Global Deep Learning Chip Market Size & Forecasts by Industry Vertical 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global Deep Learning Chip Market: Industry Vertical Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Media & Advertising
    • 7.2.2. BFSI
    • 7.2.3. IT & Telecom
    • 7.2.4. Retail
    • 7.2.5. Healthcare
    • 7.2.6. Automotive
    • 7.2.7. Others

Chapter 8. Global Deep Learning Chip Market Size & Forecasts by Region 2022-2032

  • 8.1. North America Deep Learning Chip Market
    • 8.1.1. U.S. Deep Learning Chip Market
      • 8.1.1.1. Chip Type breakdown size & forecasts, 2022-2032
      • 8.1.1.2. Technology breakdown size & forecasts, 2022-2032
      • 8.1.1.3. Industry Vertical breakdown size & forecasts, 2022-2032
    • 8.1.2. Canada Deep Learning Chip Market
  • 8.2. Europe Deep Learning Chip Market
    • 8.2.1. U.K. Deep Learning Chip Market
    • 8.2.2. Germany Deep Learning Chip Market
    • 8.2.3. France Deep Learning Chip Market
    • 8.2.4. Spain Deep Learning Chip Market
    • 8.2.5. Italy Deep Learning Chip Market
    • 8.2.6. Rest of Europe Deep Learning Chip Market
  • 8.3. Asia-Pacific Deep Learning Chip Market
    • 8.3.1. China Deep Learning Chip Market
    • 8.3.2. India Deep Learning Chip Market
    • 8.3.3. Japan Deep Learning Chip Market
    • 8.3.4. Australia Deep Learning Chip Market
    • 8.3.5. South Korea Deep Learning Chip Market
    • 8.3.6. Rest of Asia Pacific Deep Learning Chip Market
  • 8.4. Latin America Deep Learning Chip Market
    • 8.4.1. Brazil Deep Learning Chip Market
    • 8.4.2. Mexico Deep Learning Chip Market
    • 8.4.3. Rest of Latin America Deep Learning Chip Market
  • 8.5. Middle East & Africa Deep Learning Chip Market
    • 8.5.1. Saudi Arabia Deep Learning Chip Market
    • 8.5.2. South Africa Deep Learning Chip Market
    • 8.5.3. Rest of Middle East & Africa Deep Learning Chip Market

Chapter 9. Competitive Intelligence

  • 9.1. Key Company SWOT Analysis
  • 9.2. Top Market Strategies
  • 9.3. Company Profiles
    • 9.3.1. Alphabet Inc
      • 9.3.1.1. Key Information
      • 9.3.1.2. Overview
      • 9.3.1.3. Financial (Subject to Data Availability)
      • 9.3.1.4. Product Summary
      • 9.3.1.5. Market Strategies
    • 9.3.2. Qualcomm Incorporated
    • 9.3.3. Xilinx, Inc.
    • 9.3.4. Bitmain Technologies Ltd.
    • 9.3.5. Advanced Micro Devices, Inc.
    • 9.3.6. Intel Corporation
    • 9.3.7. NVIDIA Corporation
    • 9.3.8. Baidu, Inc.
    • 9.3.9. Amazon.com, Inc.
    • 9.3.10. Samsung Electronics Co. Ltd.

Chapter 10. Research Process

  • 10.1. Research Process
    • 10.1.1. Data Mining
    • 10.1.2. Analysis
    • 10.1.3. Market Estimation
    • 10.1.4. Validation
    • 10.1.5. Publishing
  • 10.2. Research Attributes