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市场调查报告书
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1534226

全球大型语言模型市场规模研究（按应用、部署、产业垂直和 2022-2032 年区域预测）

Global Large Language Model Market Size study, by Application, by Deployment, 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

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简介目录

2023年全球大语言模型（LLM）市场价值约43.5亿美元，预计2024年至2032年将以35.9%的年复合成长率（CAGR）扩张。系统接受大量文字资料的训练，以理解和产生类人语言。利用深度学习技术，法学硕士（例如 OpenAI 的 GPT-4）可以执行各种语言任务，包括翻译、摘要和问答。这些模型从大量资料集中学习上下文和细微差别，使它们能够产生连贯且上下文相关的文字。他们的应用程式涵盖从客户服务到内容创建的众多领域，显着增强了自动化语言处理能力。

全球大语言模型 (LLM) 市场由训练系统中零人工干预功能的整合所驱动，显着加速了大语言模型 (LLM) 市场的发展。这项创新允许模型自主学习和适应，无需持续的人工监督，从而提高了效率，从而大大减少了时间和资源需求。互联网资料的广泛可用性是法学硕士市场的主要推动力。这种丰富的资源是一种关键资源，使法学硕士能够从多样化和广泛的来源中学习，从而提高他们的表现和适应性。在海量互联网资料的推动下，法学硕士技术的不断改进扩大了其在众多行业的应用，从而促进了其市场采用和成长。此外，机器学习演算法的进步，特别是自然语言处理和神经网路架构的进步，对于增强大型语言模型的能力至关重要。然而，在 2024 年至 2032 年的预测期内，网路攻击的脆弱性将阻碍市场的整体需求。

全球大语言模型 (LLM) 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。 2023 年，由于该地区法学硕士技术的快速发展和进步，北美地区占据了最大的收入份额。科技、金融、医疗保健和娱乐等各个行业都是法学硕士的早期采用者，推动了需求并鼓励进一步创新，巩固了该地区的市场主导地位。此外，北美还提供广泛的资源，包括运算基础设施、资料和协作机会。此外，在其广阔而多样化的市场以及不断增长的数位人口的推动下，亚太地区预计将在预测期内显着增长。该地区的市场扩张为各行业和消费者群体采用法学硕士提供了充足的机会。亚太地区专门从事人工智慧和自然语言处理的创新新创公司和科技公司的出现也促进了法学硕士的发展和采用，为市场提供了独特的解决方案。

目录

第 1 章：全球大语言模型 (LLM) 市场执行摘要

  • 全球大语言模型 (LLM) 市场规模及预测 (2022-2032)
  • 区域概要
  • 分部摘要
    • 按申请
    • 按部署
    • 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：全球大语言模型 (LLM) 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 3 章：全球大语言模型 (LLM) 市场动态

  • 市场驱动因素
    • 训练系统中零人为干预的兴起
    • 丰富的网路数据
    • 机器学习演算法的进步
  • 市场挑战
    • 网路攻击的脆弱性
  • 市场机会
    • 亚太地区的采用率不断提高
    • 增加各行业的应用

第 4 章：全球大语言模型 (LLM) 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
    • 波特的五力影响分析
  • 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：全球大语言模型 (LLM) 市场规模与预测：按应用分类 - 2022-2032

  • 细分仪表板
  • 全球大型语言模型 (LLM) 市场：2022 年和 2032 年应用收入趋势分析
    • 客户服务
    • 内容生成
    • 情绪分析
    • 程式码生成
    • 聊天机器人和虚拟助理
    • 语言翻译

第 6 章：全球大型语言模型 (LLM) 市场规模与预测：按部署划分 - 2022-2032

  • 细分仪表板
  • 全球大型语言模型 (LLM) 市场：2022 年和 2032 年部署收入趋势分析
    • 云
    • 本地

第 7 章：全球大语言模型 (LLM) 市场规模与预测：按产业垂直 - 2022-2032

  • 细分仪表板
  • 全球大型语言模型 (LLM) 市场：2022 年和 2032 年产业垂直收入趋势分析
    • 卫生保健
    • 金融
    • 零售及电子商务
    • 媒体和娱乐
    • 其他（教育、法律、游戏）

第 8 章：全球大语言模型 (LLM) 市场规模与预测：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
  • 亚太地区
    • 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
    • Alibaba Group Holding Limited
      • 关键讯息
      • 概述
      • 财务（视数据可用性而定）
      • 产品概要
      • 市场策略
    • Amazon.com, Inc.
    • Baidu, Inc.
    • Huawei Technologies Co., Ltd.
    • Meta Platforms, Inc.
    • Tencent Holdings Limited
    • Google LLC
    • Microsoft Corporation
    • OpenAI LP
    • Yandex

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 Large Language Model (LLM) Market was valued at approximately USD 4.35 billion in 2023 and is expected to expand at a compound annual growth rate (CAGR) of 35.9% from 2024 to 2032. Large Language Model (LLM) is an advanced artificial intelligence system trained on extensive text data to understand and generate human-like language. Utilizing deep learning techniques, LLMs, such as OpenAI's GPT-4, can perform various language tasks, including translation, summarization, and question-answering. These models learn context and nuances from vast datasets, enabling them to produce coherent and contextually relevant text. Their applications span numerous fields, from customer service to content creation, significantly enhancing automated language processing capabilities.

The Global Large Language Model (LLM) Market is driven by integration of zero human intervention features in training systems is significantly accelerating the large language models (LLMs) market. This innovation enhances efficiency by allowing models to autonomously learn and adapt without constant manual oversight, thereby reducing time and resource demands substantially. The extensive availability of internet data is a major propellant for the LLM market. This abundance serves as a critical resource, enabling LLMs to learn from diverse and vast sources, thereby enhancing their performance and adaptability. This continuous improvement in LLM technology, driven by the vast internet data, broadens their applications across numerous industries, thereby boosting their market adoption and growth. Moreover, Advancements in machine learning algorithms, particularly in natural language processing and neural network architectures, are pivotal in enhancing the capabilities of large language models. However, vulnerability to cyberattacks is going to impede the overall demand for the market during the forecast period 2024-2032.

The key regions considered for the Global Large Language Model (LLM) Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. In 2023, North America held the largest revenue share owing to rapid evolution and advancement of LLM technology in the region. Various sectors such as tech, finance, healthcare, and entertainment are early adopters of LLMs, driving demand and encouraging further innovation, solidifying the region's market dominance. Moreover, North America provides access to extensive resources including computing infrastructure, data, and collaboration opportunities. Furthermore, Asia Pacific is expected to witness significant growth over the forecast period, driven by its vast and diverse market with a growing digital population. The region's market expansion presents ample opportunities for LLM adoption across various industries and consumer segments. The emergence of innovative startups and tech companies specializing in AI and natural language processing in Asia Pacific is also contributing to the development and adoption of LLMs, offering unique solutions to the market.

Major market players included in this report are:

  • Alibaba Group Holding Limited
  • Amazon.com, Inc.
  • Baidu, Inc.
  • Huawei Technologies Co., Ltd.
  • Meta Platforms, Inc.
  • Tencent Holdings Limited
  • Google LLC
  • Microsoft Corporation
  • OpenAI LP
  • Yandex

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

By Application:

  • Customer Service
  • Content Generation
  • Sentiment Analysis
  • Code Generation
  • Chatbots and Virtual Assistant
  • Language Translation

By Deployment:

  • Cloud
  • On-premises

By Industry Vertical:

  • Healthcare
  • Finance
  • Retail and E-commerce
  • Media and Entertainment
  • Others (Education, Legal, Gaming)

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 Large Language Model (LLM) Market Executive Summary

  • 1.1. Global Large Language Model (LLM) Market Size & Forecast (2022-2032)
  • 1.2. Regional Summary
  • 1.3. Segmental Summary
    • 1.3.1. By Application
    • 1.3.2. By Deployment
    • 1.3.3. By Industry Vertical
  • 1.4. Key Trends
  • 1.5. Recession Impact
  • 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Large Language Model (LLM) 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 Large Language Model (LLM) Market Dynamics

  • 3.1. Market Drivers
    • 3.1.1. Rise of Zero Human Intervention in Training Systems
    • 3.1.2. Abundant Availability of Internet Data
    • 3.1.3. Advancements in Machine Learning Algorithms
  • 3.2. Market Challenges
    • 3.2.1. Vulnerability to Cyberattacks
  • 3.3. Market Opportunities
    • 3.3.1. Growing Adoption in Asia Pacific
    • 3.3.2. Increasing Applications Across Various Industries

Chapter 4. Global Large Language Model (LLM) 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 Large Language Model (LLM) Market Size & Forecasts by Application 2022-2032

  • 5.1. Segment Dashboard
  • 5.2. Global Large Language Model (LLM) Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 5.2.1. Customer Service
    • 5.2.2. Content Generation
    • 5.2.3. Sentiment Analysis
    • 5.2.4. Code Generation
    • 5.2.5. Chatbots and Virtual Assistant
    • 5.2.6. Language Translation

Chapter 6. Global Large Language Model (LLM) Market Size & Forecasts by Deployment 2022-2032

  • 6.1. Segment Dashboard
  • 6.2. Global Large Language Model (LLM) Market: Deployment Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 6.2.1. Cloud
    • 6.2.2. On-premises

Chapter 7. Global Large Language Model (LLM) Market Size & Forecasts by Industry Vertical 2022-2032

  • 7.1. Segment Dashboard
  • 7.2. Global Large Language Model (LLM) Market: Industry Vertical Revenue Trend Analysis, 2022 & 2032 (USD Billion)
    • 7.2.1. Healthcare
    • 7.2.2. Finance
    • 7.2.3. Retail and E-commerce
    • 7.2.4. Media and Entertainment
    • 7.2.5. Others (Education, Legal, Gaming)

Chapter 8. Global Large Language Model (LLM) Market Size & Forecasts by Region 2022-2032

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

Chapter 9. Competitive Intelligence

  • 9.1. Key Company SWOT Analysis
  • 9.2. Top Market Strategies
  • 9.3. Company Profiles
    • 9.3.1. Alibaba Group Holding Limited
      • 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. Amazon.com, Inc.
    • 9.3.3. Baidu, Inc.
    • 9.3.4. Huawei Technologies Co., Ltd.
    • 9.3.5. Meta Platforms, Inc.
    • 9.3.6. Tencent Holdings Limited
    • 9.3.7. Google LLC
    • 9.3.8. Microsoft Corporation
    • 9.3.9. OpenAI LP
    • 9.3.10. Yandex

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