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1534226

全球大型語言模型市場規模研究（按應用、部署、產業垂直和 2022-2032 年區域預測）

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個工作天內

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簡介目錄

2023年全球大語言模型（LLM）市場價值約43.5億美元，預計2024年至2032年將以35.9%的年複合成長率（CAGR）擴張。系統接受大量文字資料的訓練，以理解和產生類人語言。利用深度學習技術，法學碩士（例如 OpenAI 的 GPT-4）可以執行各種語言任務，包括翻譯、摘要和問答。這些模型從大量資料集中學習上下文和細微差別，使它們能夠產生連貫且上下文相關的文字。他們的應用程式涵蓋從客戶服務到內容創建的眾多領域，顯著增強了自動化語言處理能力。

全球大語言模型 (LLM) 市場由訓練系統中零人工干預功能的整合所驅動，顯著加速了大語言模型 (LLM) 市場的發展。這項創新允許模型自主學習和適應，無需持續的人工監督，從而提高了效率，從而大大減少了時間和資源需求。網際網路資料的廣泛可用性是法學碩士市場的主要推動力。這種豐富的資源是一種關鍵資源，使法學碩士能夠從多樣化和廣泛的來源中學習，從而提高他們的表現和適應性。在海量網際網路資料的推動下，法學碩士技術的不斷改進擴大了其在眾多行業的應用，從而促進了其市場採用和成長。此外，機器學習演算法的進步，特別是自然語言處理和神經網路架構的進步，對於增強大型語言模型的能力至關重要。然而，在 2024 年至 2032 年的預測期內，網路攻擊的脆弱性將阻礙市場的整體需求。

全球大語言模型 (LLM) 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。 2023 年，由於該地區法學碩士技術的快速發展和進步，北美地區佔據了最大的收入佔有率。科技、金融、醫療保健和娛樂等各個行業都是法學碩士的早期採用者，推動了需求並鼓勵進一步創新，鞏固了該地區的市場主導地位。此外，北美還提供廣泛的資源，包括運算基礎設施、資料和協作機會。此外，在其廣闊而多樣化的市場以及不斷成長的數位人口的推動下，亞太地區預計將在預測期內顯著成長。該地區的市場擴張為各行業和消費者群體採用法學碩士提供了充足的機會。亞太地區專門從事人工智慧和自然語言處理的創新新創公司和科技公司的出現也促進了法學碩士的發展和採用，為市場提供了獨特的解決方案。

目錄

第 1 章：全球大語言模型 (LLM) 市場執行摘要

  • 全球大語言模型 (LLM) 市場規模及預測 (2022-2032)
  • 區域概要
  • 分部摘要
    • 按申請
    • 按部署
    • 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：全球大語言模型 (LLM) 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：全球大語言模型 (LLM) 市場動態

  • 市場促進因素
    • 訓練系統中零人為干預的興起
    • 豐富的網路數據
    • 機器學習演算法的進步
  • 市場挑戰
    • 網路攻擊的脆弱性
  • 市場機會
    • 亞太地區的採用率不斷提高
    • 增加各行業的應用

第 4 章：全球大語言模型 (LLM) 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
    • 波特的五力影響分析
  • 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：全球大語言模型 (LLM) 市場規模與預測：按應用分類 - 2022-2032

  • 細分儀表板
  • 全球大型語言模型 (LLM) 市場：2022 年和 2032 年應用收入趨勢分析
    • 客戶服務
    • 內容生成
    • 情緒分析
    • 程式碼生成
    • 聊天機器人和虛擬助理
    • 語言翻譯

第 6 章：全球大型語言模型 (LLM) 市場規模與預測：按部署分類 - 2022-2032

  • 細分儀表板
  • 全球大型語言模型 (LLM) 市場：2022 年和 2032 年部署收入趨勢分析
    • 雲
    • 本地

第 7 章：全球大語言模型 (LLM) 市場規模與預測：按產業垂直 - 2022-2032

  • 細分儀表板
  • 全球大型語言模型 (LLM) 市場：2022 年和 2032 年產業垂直收入趨勢分析
    • 衛生保健
    • 金融
    • 零售及電子商務
    • 媒體和娛樂
    • 其他（教育、法律、遊戲）

第 8 章：全球大語言模型 (LLM) 市場規模與預測：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
  • 亞太地區
    • 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
    • Alibaba Group Holding Limited
      • 關鍵訊息
      • 概述
      • 財務（視數據可用性而定）
      • 產品概要
      • 市場策略
    • 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 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