机器学习：主题智能

Machine Learning - Thematic Intelligence

出版日期: 2022年12月07日 | 出版商:

GlobalData | 英文 76 Pages | 订单完成后即时交付

价格

※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。

简介目录

机器学习是人工智能 (AI) 的一个子集，它允许计算机系统在不明确编程的情况下从数据中学习和改进。机器学习是目前被企业采用的AI最实际的应用领域。

公司可以使用无代码/低代码和 MLaaS（机器学习即服务）平台来满足没有广泛编程技能的人的需求，而不是从头开始僱用程序员和设计机器学习工具。你可以设计一个适合的系统。因此，机器学习操作 (MLOps) 在以高标准实施和监控系统方面变得越来越普遍。

这家总部位于美国的机器学习公司在过去十年中通过 3,038 笔风险融资交易筹集了总计 579.6 亿美元的资金。

在这份报告中，我们分析了全球机器学习 (ML) 的技术和市场趋势，概述了该技术、主要应用领域、近期技术发展和引进趋势、整体市场规模趋势，我们正在调查相关专利申请和註册趋势，细分趋势（硬件、软件（大数据管理、机器学习技术）、服务（平台、MLaaS、图书馆）等）。

内容

执行摘要
市场进入者
技术概览
趋势
技术趋势
宏观经济趋势
监管趋势
行业分析
市场规模和增长率预测
併购 (M&A)
风险投资
专利趋势
公司申请趋势
招聘趋势
用例
时间表
价值链
硬件
软件
服务
公司
部门记分卡
应用软件记分卡
云服务记分卡
词彙表
参考文献
主题研究的分析方法
关于全球数据
联繫人

简介目录

Product Code: GDTMT-TR-S379

Machine learning is a subset of artificial intelligence (AI) that allows computer systems to learn and improve from data without being explicitly programmed. Machine learning is the most practical application of AI currently available for enterprise adoption.

Key Highlights

GlobalData forecasts the global AI market will be worth $136 billion in 2026. Specialist AI applications will account for the largest proportion of 2026 revenue at 37%, followed by AI consulting and support services at 30%. AI platforms will record the fastest revenue growth between 2021 and 2026 (a CAGR of 18%).
Instead of companies employing programmers to design machine learning tools from scratch, nocode/low-code and machine learning as a service (MLaaS) platforms allow those without extensive programming ability to design systems tailored to their needs. This has also led to the popularity of machine learning operations (MLOps) to ensure systems are implemented and monitored to a high standard.
AI is increasingly involved in life-changing decisions like welfare payments, mortgage approvals, and medical diagnoses. Consequently, transparency and explainability have become essential. Some key AI frameworks driving transparency in the sector include IBM's open-source AI 360 tool kit and Rulex's Logic Leaning Machine (LLM).
The main areas driving AI M&A deals are NLP, automated driving, MLaaS, and enterprise predictive analytics.
US-based machine learning companies have raised a total of $57,960 million through 3,038 venture financing deals in the last 10 years.

Scope

This report provides an overview of the machine learning theme.
It identifies the key trends impacting growth of the theme over the next 12 to 24 months.
It includes a comprehensive industry analysis, including market size and growth forecasts for AI hardware, AI platforms, AI consulting and support services, and specialized AI applications.
The detailed value chain breaks down machine learning into three areas: hardware, software (big data management and machine learning techniques), and services (platforms, MLaaS, and libraries).

Reasons to Buy

Machine learning will benefit all enterprises in some capacity, with potential advantages including automation, trend and pattern recognition, process improvement, and forecasting. This report will help readers make sense of the machine learning theme, understand training techniques and leading algorithms, the business benefits, identify the leading vendors and startups, and understand MLaaS, MLOps, and machine learning libraries.