Purpose

Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the potential to generate numerous business opportunities in the future. However, most related studies have examined patent grants granted by or patent applications filed to major patent offices; few studies have employed the perspective of standard-essential patents (SEPs) from a holistic technical view. In addition, because few studies have explored the status signals of countries in relation to SEPs, the present study integrated “country” into the model and determined differences among countries in terms of their technological focus.

Design/methodology/approach

In this study, through patent technological network analysis in various periods, the author not only observed the focus fields of AI-related SEPs but also examined temporal trends to determine technical development trends.

Findings

This study identified technologies that have been key players in the SEP network in recent years; these technologies were centered on electric digital data processing, recognition of data and transmission of digital information. Moreover, many of these technologies have been applied in areas such as management and commerce and radio navigation. Furthermore, the USA plays a crucial role in the global development of AI technical network.

Originality/value

This study constructs a technical network model to identify key technologies and trends that can serve as a reference for national research and development resource allocation.

中文翻译：

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标准必要专利中的人工智能技术趋势

目的

定义关键的人工智能（AI）技术尤其重要，因为AI应用程序涉及多个技术领域的发展，并且有可能在未来产生大量商机。但是，大多数相关研究都研究了由主要专利局授予的专利授权或提交给主要专利局的专利申请。从整体技术角度来看，很少有研究采用标准必要专利（SEP）的观点。此外，由于很少有研究探讨与SEP相关的国家的状态信号，因此本研究将“国家”整合到模型中，并确定了国家在技术重点方面的差异。

设计/方法/方法

在这项研究中，作者通过各个时期的专利技术网络分析，不仅观察了AI相关SEP的关注领域，还研究了时间趋势以确定技术发展趋势。

发现

这项研究确定了近年来成为SEP网络关键参与者的技术。这些技术集中于电子数字数据处理，数据识别和数字信息传输。而且，这些技术中的许多已被应用于诸如管理和商业以及无线电导航的领域。此外，美国在AI技术网络的全球发展中起着至关重要的作用。

创意/价值

这项研究构建了一个技术网络模型，以识别可为国家研发资源分配提供参考的关键技术和趋势。