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人工智能

市场调查报告书

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1544541

多模式人工智慧市场、机会、成长动力、产业趋势分析与预测，2024-2032

Multimodal AI Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

出版日期: 2024年07月01日 | 出版商:

Global Market Insights Inc. | 英文 410 Pages | 商品交期: 2-3个工作天内

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简介目录

在视讯资料分析的重大进步和对创新人工智慧服务不断增长的需求的推动下，2024年至2032年，全球多模式人工智慧市场规模的复合年增长率将超过30%。领先科技公司不断推出的创新产品支持了市场成长。例如，2024 年 3 月，Apple 推出了 MM1，这是一套旨在处理图像和文字的多模式模型。这些模型具有多达 300 亿个参数，与 Google Gemini 的早期版本相当。 MM1 可以遵循影像指令并进行推理，作为其多模式功能的一部分。

多模态人工智慧整合了文字、音讯和视讯等各种资料类型，透过提供更全面、更准确的洞察，正在为产业带来革命性的变化。这一增长是由持续的研究和开发以及医疗保健、金融和零售等领域的应用不断增加所推动的。

整个多模态人工智慧产业根据组件、技术、资料模态、类型、产业垂直和区域进行分类。

就资料形态而言，视讯资料领域将成为 2024 年至 2032 年的主要成长资料。电脑视觉和深度学习技术的进步正在增强人工智慧系统更有效地分析和解释视讯内容的能力。这种功能在监控、自动驾驶汽车和基于视讯的分析等应用中特别有价值，刺激了对结合视讯资料的多模式人工智慧解决方案的需求。

就零件而言，服务部门预计在预测期内大幅成长。随着多模式人工智慧技术的发展，对咨询、整合和支援等相关服务的需求不断增加。组织正在寻求实施和优化人工智慧系统的专业知识，以充分利用多模式资料的潜力。这包括客製化解决方案以满足特定业务需求并确保与现有基础设施的无缝整合。人工智慧系统日益复杂以及对专业技能的需求正在推动多模式人工智慧市场中服务组件的扩展。

2024年至2032年，欧洲多模式人工智慧市场将呈现显着的复合年增长率。该地区对创新和技术进步的关注正在促进各行业多模式人工智慧应用的成长。此外，人工智慧在医疗保健、汽车和金融等领域的日益普及正在推动对多模式解决方案的需求。欧洲致力于推动人工智慧技术和满足监管要求，使该地区成为全球多模式人工智慧市场的关键参与者。

产业生态系统分析
供应商矩阵
利润率分析
技术与创新格局
专利分析
重要新闻和倡议
监管环境
衝击力
- 成长动力
  - 增强的人机交互
  - 产业特定应用
  - 5G和边缘运算
  - 企业投资和合作伙伴关係
  - 自然语言处理 (NLP) 的进步
- 产业陷阱与挑战
  - 资料隐私和安全问题
  - 偏见和公平问题
成长潜力分析
波特的分析
PESTEL分析

第 4 章：竞争格局

介绍
公司市占率分析
竞争定位矩阵
战略展望矩阵

第 5 章：市场估计与预测：按组成部分，2021 - 2032 年

解决方案
服务

第 6 章：市场估计与预测：按资料模式，2021 - 2032

影像资料
文字资料
语音和语音资料
视讯资料
音讯资料

第 7 章：市场估计与预测：按技术分类，2021 - 2032

机器学习
自然语言处理
电脑视觉
情境意识
物联网

第 8 章：市场估计与预测：按类型，2021 - 2032

生成式多模式人工智慧
翻译性多模式人工智慧
解释性多模式人工智慧
互动式多模式人工智慧

第 9 章：市场估计与预测：按产业垂直划分，2021 - 2032 年

BFSI
零售与电子商务
资讯科技和电信
政府和公共部门
卫生保健
製造业
媒体和娱乐
其他的

第 10 章：市场估计与预测：按地区，2021 - 2032

主要趋势
北美洲
- 我们
- 加拿大
欧洲
- 英国
- 德国
- 法国
- 义大利
- 西班牙
- 欧洲其他地区
亚太地区
- 中国
- 印度
- 日本
- 韩国
- 澳新银行
- 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
MEA
- 阿联酋
- 南非
- 沙乌地阿拉伯
- MEA 的其余部分

第 11 章：公司简介

Aiberry Inc.
Aimesoft Inc.
Amazon Web Services, Inc.
Archetype AI Inc.
Beewant SAS
Google Inc.
Habana Labs Inc.
Hoppr Inc.
Inworld AI Inc.
International Business Machines Corporation (IBM)
Jina AI GmbH
Jiva.ai Ltd.
Microsoft Corporation
Mobius Labs Inc.
Modality.AI Inc.
Multimodal Inc.
Neuraptic AI S.L.
Newsbridge SAS
OpenAI Inc.
OpenStream AI Inc.
Owlbot.AI Inc.
Perceiv AI Inc.
Reka AI Inc.
Runway AI Inc.
Stability AI Ltd.

简介目录

Product Code: 10071

Global Multimodal AI Market size will experience over 30% CAGR from 2024 to 2032, fueled by significant advancements in video data analysis and the growing demand for innovative AI services. The rising innovative launches by leading tech companies support market growth. For instance, in March 2024, Apple introduced MM1, a suite of multimodal models designed to process both images and text. The models featured up to 30 billion parameters and were on par with the early versions of Google Gemini. MM1 could follow instructions and reasoning with images as part of its multimodal functions.

Multimodal AI integrating various data types, such as text, audio, and video, is revolutionizing industries by providing more comprehensive and accurate insights. This growth is driven by ongoing research and development, alongside increasing applications in sectors such as healthcare, finance, and retail.

The overall Multimodal AI Industry is classified based on the component, technology, data modality, type, industry vertical, and region.

In terms of data modality, the video data segment will be a major growth driver from 2024 to 2032. Video data is becoming increasingly crucial as businesses and organizations seek to leverage visual information for insights and decision-making. Advances in computer vision and deep learning technologies are enhancing the ability of AI systems to analyze and interpret video content more effectively. This capability is particularly valuable in applications such as surveillance, autonomous vehicles, and video-based analytics, fueling demand for multimodal AI solutions incorporating video data.

Regarding components, the services segment is poised for substantial growth over the forecast period. As multimodal AI technologies evolve, the demand for related services such as consulting, integration, and support is rising. Organizations are seeking expertise in implementing and optimizing AI systems to harness the full potential of multimodal data. This includes customizing solutions to meet specific business needs and ensuring seamless integration with existing infrastructure. The growing complexity of AI systems and the need for specialized skills are driving the expansion of the services component in the multimodal AI market.

Europe multimodal AI market will exhibit a significant CAGR from 2024 to 2032. European countries are increasingly investing in AI research and development, supported by favorable regulatory frameworks and government initiatives. The region's focus on innovation and technological advancement is fostering the growth of multimodal AI applications across various industries. Additionally, the growing adoption of AI in sectors such as healthcare, automotive, and finance is driving demand for multimodal solutions. Europe's commitment to advancing AI technology and addressing regulatory requirements is positioning the region as a key player in the global multimodal AI market.

Chapter 1 Methodology and Scope

1.1 Market scope and definition
1.2 Base estimates and calculations
1.3 Forecast calculation
1.4 Data sources
- 1.4.1 Primary
- 1.4.2 Secondary
  - 1.4.2.1 Paid sources
  - 1.4.2.2 Public sources

Chapter 2 Executive Summary

2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Vendor matrix
3.3 Profit margin analysis
3.4 Technology and innovation landscape
3.5 Patent analysis
3.6 Key news and initiatives
3.7 Regulatory landscape
3.8 Impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 Enhanced human-machine interaction
  - 3.8.1.2 Industry-specific applications
  - 3.8.1.3 5G and edge computing
  - 3.8.1.4 Corporate investments and partnerships
  - 3.8.1.5 Advancements in natural language processing (NLP)
- 3.8.2 Industry pitfalls and challenges
  - 3.8.2.1 Data privacy and security concerns
  - 3.8.2.2 Bias and fairness issues
3.9 Growth potential analysis
3.10 Porter's analysis
- 3.10.1 Supplier power
- 3.10.2 Buyer power
- 3.10.3 Threat of new entrants
- 3.10.4 Threat of substitutes
- 3.10.5 Industry rivalry
3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2032 (USD Million)

5.1 Solution
5.2 Service

Chapter 6 Market estimates and forecast, By Data Modality, 2021 - 2032 (USD Million)

6.1 Image data
6.2 Text data
6.3 Speech and voice data
6.4 Video data
6.5 Audio data

Chapter 7 Market estimates and forecast, By Technology, 2021 - 2032 (USD Million)

7.1 Machine learning
7.2 Natural language processing
7.3 Computer vision
7.4 Context awareness
7.5 Internet of things

Chapter 8 Market estimates and forecast, By Type, 2021 - 2032 (USD Million)

8.1 Generative multimodal AI
8.2 Translative multimodal AI
8.3 Explanatory multimodal AI
8.4 Interactive multimodal AI

Chapter 9 Market estimates and forecast, By Industry Vertical, 2021 - 2032 (USD Million)

9.1 BFSI
9.2 Retail and E-Commerce
9.3 IT and telecommunication
9.4 Government and public sector
9.5 Healthcare
9.6 Manufacturing
9.7 Media and Entertainment
9.8 Others

Chapter 10 Market Estimates and Forecast, By Region, 2021 - 2032 (USD Million)

10.1 Key trends
10.2 North America
- 10.2.1 U.S.
- 10.2.2 Canada
10.3 Europe
- 10.3.1 UK
- 10.3.2 Germany
- 10.3.3 France
- 10.3.4 Italy
- 10.3.5 Spain
- 10.3.6 Rest of Europe
10.4 Asia Pacific
- 10.4.1 China
- 10.4.2 India
- 10.4.3 Japan
- 10.4.4 South Korea
- 10.4.5 ANZ
- 10.4.6 Rest of Asia Pacific
10.5 Latin America
- 10.5.1 Brazil
- 10.5.2 Mexico
- 10.5.3 Rest of Latin America
10.6 MEA
- 10.6.1 UAE
- 10.6.2 South Africa
- 10.6.3 Saudi Arabia
- 10.6.4 Rest of MEA