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市场调查报告书
商品编码
1534224

全球深度学习晶片市场规模研究（按晶片类型、技术、垂直产业和 2022-2032 年区域预测）

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个工作天内

价格
简介目录

2023 年全球深度学习晶片市场价值约为110.5 亿美元，预计在2024 年至2032 年的预测期内将以35.27% 的复合年增长率强劲增长。的专用硬件，特别是深度学习演算法。这些晶片优化了神经网路中涉及的复杂运算，从而提高了效能和效率。主要功能包括平行处理能力、高记忆体频宽和低功耗。该市场的主要参与者包括 NVIDIA、英特尔和谷歌，它们各自为自动驾驶汽车、医学成像和自然语言处理等各种应用开发先进的晶片。对人工智慧驱动解决方案不断增长的需求推动了深度学习晶片产业的快速成长。

全球深度学习晶片市场是由量子运算的出现和深度学习晶片在机器人领域的不断部署所推动的。深度学习晶片在机器人技术中的日益整合增强了它们处理复杂资料和执行复杂任务的能力，从而推动了市场扩张。这些晶片使机器人能够从资料中学习、适应新情况并随着时间的推移提高性能，这使得它们在製造、医疗保健和自主系统等行业中发挥着至关重要的作用。这种双重影响极大地推动了市场的成长轨迹。此外，能够自我开发和自主控制的自主机器人数量不断增加，带来了巨大的成长机会。然而，该行业面临技术专业人才短缺等挑战。测试、错误修復和云端实施等任务主要由深度学习晶片管理，但缺乏必要的专业知识。

全球深度学习晶片市场研究考虑的关键区域包括亚太地区、北美、欧洲、拉丁美洲和世界其他地区。预计到 2023 年，亚太地区的复合年增长率将达到最高，这表明深度学习技术在各种应用中的快速采用和整合。这一成长的推动因素包括人工智慧投资的增加、技术基础设施的扩大以及医疗保健、汽车和金融等行业对高级分析的需求不断增长。中国、印度、日本和澳洲等主要市场正在引领这一趋势，利用深度学习来提高各自领域的创新和效率。

报告中包括的主要市场参与者有：

  • 字母公司
  • 高通公司
  • 赛灵思公司
  • 比特大陆科技有限公司
  • 超微半导体公司
  • 英特尔公司
  • 英伟达公司
  • 百度公司
  • 亚马逊公司
  • 三星电子有限公司

市场的详细细分和细分市场解释如下：

目录

第 1 章：全球深度学习晶片市场执行摘要

  • 全球深度学习晶片市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 按晶片类型
    • 依技术
    • 按行业分类
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球深度学习晶片市场定义与研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第三章：全球深度学习晶片市场动态

  • 市场驱动因素
    • 量子计算的出现
    • 增强机器人技术的实施
  • 市场挑战
    • 缺乏熟练劳动力
  • 市场机会
    • 自主机器人的出现
    • 各行业的采用率不断提高

第四章：全球深度学习晶片市场产业分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的未来方法
    • 波特的 5 力影响分析
  • PESTEL分析
    • 政治的
    • 经济
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 最佳制胜策略
  • 颠覆性趋势
  • 产业专家视角
  • 分析师推荐与结论

第 5 章：全球深度学习晶片市场规模与预测：按晶片类型 - 2022-2032

  • 细分仪表板
  • 全球深度学习晶片市场：2022年&2032年晶片类型营收趋势分析
    • 图形处理器
    • 专用积体电路
    • FPGA
    • 中央处理器
    • 其他的

第 6 章：全球深度学习晶片市场规模与预测：按技术分类 - 2022-2032

  • 细分仪表板
  • 全球深度学习晶片市场：2022年及2032年技术收入趋势分析
    • 系统单晶片 (SoC)
    • 系统级封装 (SIP)
    • 多晶片模组
    • 其他的

第 7 章：全球深度学习晶片市场规模与预测：按行业垂直分类 - 2022-2032

  • 细分仪表板
  • 全球深度学习晶片市场：2022年及2032年产业垂直收入趋势分析
    • 媒体与广告
    • BFSI
    • 资讯科技与电信
    • 零售
    • 卫生保健
    • 汽车
    • 其他的

第 8 章：全球深度学习晶片市场规模及预测：按地区 - 2022-2032

  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 9 章：竞争情报

  • 重点企业SWOT分析
  • 顶级市场策略
  • 公司简介
    • Alphabet Inc
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • 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：研究过程

  • 研究过程
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

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