2021
DOI: 10.36897/jme/134245
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Machine Learning in Cyber-Physical Systems and Manufacturing Singularity – It Does Not Mean Total Automation, Human is Still in the Centre: Part II – In-CPS and a View from Community on Industry 4.0 Impact on Society

Abstract: In many discourses, popular as well as scientific, it is suggested that the "massive" use of Artificial Intelligence (AI), including Machine Learning (ML), and reaching the point of "singularity" through so-called Artificial General Intelligence (AGI), and Artificial Super-Intelligence (ASI), will completely exclude humans from decision making, resulting in total dominance of machines over human race. Speaking in terms of manufacturing systems, it would mean that the intelligence and total automation would be … Show more

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Cited by 10 publications
(4 citation statements)
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“…With this approach, current diagnostics and monitoring of feed axes can become more available in the industry. In addition, It is possible to make automatic fault diagnoses by classifying the results obtained in this study with different machine learning methods in the future [20][21]. In addition to these, In our studies, it is seen that weight changes do not affect the results, but force changes do.…”
Section: Discussionmentioning
confidence: 52%
“…With this approach, current diagnostics and monitoring of feed axes can become more available in the industry. In addition, It is possible to make automatic fault diagnoses by classifying the results obtained in this study with different machine learning methods in the future [20][21]. In addition to these, In our studies, it is seen that weight changes do not affect the results, but force changes do.…”
Section: Discussionmentioning
confidence: 52%
“…It is worth to mention about automated machine learning, which can save time and money spent on searching effective machine learning methods. Searching for thermal error modelling method may be supported by double-loop learning [54], n-loop learning [55,56]. F. Hutter et al performed review of automated machine learning (AutoML) methods [57].…”
Section: Gist Of Machine Learningmentioning
confidence: 99%
“…Authors discuss different approaches to intelligent data analysis in the manufacturing process. Putnik et al proposed an intelligent machine architecture with multiple learning meta-levels [1], and noticed that artificial intelligence is useful as a method for manufacturing control and supporting the decision making process based on simulation [2]. Uhlmann et al [3] proposed integration of ANN models in the process of accuracy improvement of industrial robots.…”
Section: Introductionmentioning
confidence: 99%