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Analyses of the Technological Accumulation over the 2ndand the 3rdAI Boom and the Issues Related to AI Adoption by Firms

机译:第2次和第3次AI繁荣中的技术积累以及与企业采用AI有关的问题的分析

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Although AI was proposed by J. McCarthy back in 1956, 60 years later, we are beginning to witness a surge of interest in the practical applications of AI in many sectors. However, the actual adoption rate of AI in businesses has been quite low. The current 3rd AI boom follows the 2nd AI boom in the 1980s which focused mainly on expert systems. In this paper, an attempt is made to analyze the technological accumulation process from the 2ndto the 3rd AI boom and to identify forthcoming key application areas. The methodology is based on a 3 step approach. In the first step, a bibliometric analyses of Artificial Intelligence was carried out to analyze the technological accumulation during the 2nd and the 3rd AI boom. Having done the desk work and interviewed several experts in AI, we decided that 2013 was the year which marked the boundary between the two AI booms. A bibliometric analyses based on countries and institutions over the 2 periods was followed by co-occurrence analyses of the author keywords in the 2 periods, before and after 2013. In the third stage, interviews were carried out with some corporate members to do a qualitative analysis on the possible application areas of AI and issues to be solved for adopting AI were identified. The results showed that in the 3rd AI boom, machine learning, deep learning, genetic algorithm have been identified as the key technologies. Furthermore, prediction, forecasting, data mining, fault diagnosis, pattern recognition were identified as important areas in the 3rd AI boom. It was also revealed that firms' R&D has been changing to focus more on AI applications.
机译:尽管AI由J. McCarthy于1956年提出,但60年后,我们开始看到人们对AI在许多领域的实际应用产生了浓厚的兴趣。但是,AI在企业中的实际采用率一直很低。当前的第三次AI繁荣是继1980年代的第二次AI繁荣之后,第二次AI繁荣主要集中在专家系统上。本文试图从两个方面分析技术积累过程。 nd 第三届AI繁荣,并确定即将到来的关键应用领域。该方法基于三步法。第一步,对人工智能进行了文献计量分析,以分析第二次和第三次AI繁荣期间的技术积累。完成案头工作并采访了几位AI专家之后,我们决定2013年是标志着两次AI繁荣之间界限的一年。在两个时期内对国家和机构进行了文献计量分析,然后在2013年之前和之后的两个时期内对作者关键字进行了同时出现分析。在第三阶段,与一些公司成员进行了访谈,以进行定性分析确定了对AI可能的应用领域的分析以及采用AI所要解决的问题。结果表明,在第三次AI繁荣中,机器学习,深度学习,遗传算法已被确定为关键技术。此外,预测,预测,数据挖掘,故障诊断,模式识别被确定为第三次AI繁荣的重要领域。还显示,公司的研发已发生变化,以更加专注于AI应用程序。

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