MACHINE LEARNING IN CYBER-PHYSICAL SYSTEMS AND MANUFACTURING SINGULARITY – IT DOES NOT MEAN TOTAL AUTOMATION, HUMAN IS STILL IN THE CENTRE: Part I – MANUFACTURING SINGULARITY AND AN INTELLIGENT MACHINE ARCHITECTURE

Q2 Engineering Journal of Machine Engineering Pub Date : 2020-12-04 DOI:10.36897/jme/131000
G. Putnik, Vaibhav Shah, Zlata Putnik, Luís Ferreira
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引用次数: 6

Abstract

In many popular, as well scientific, discourses it is suggested that the “massive” use of Artificial Intelligence, including Machine Learning, 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 there will be achieved intelligent and total automation (once the humans will be excluded). The hypothesis presented in this paper is that there is a limit of AI/ML autonomy capacity, and more concretely, that the ML algorithms will be not able to became totally autonomous and, consequently, that the human role will be indispensable. In the context of the question, the authors of this paper introduce the notion of the manufacturing singularity and an intelligent machine architecture towards the manufacturing singularity, arguing that the intelligent machine will be always human dependent, and that, concerning the manufacturing, the human will remain in the centre of Cyber-Physical Systems (CPS) and in I4.0. The methodology to support this argument is inductive, similarly to the methodology applied in a number of texts found in literature, and based on computational requirements of inductive inference based machine learning. The argumentation is supported by several experiments that demonstrate the role of human within the process of machine learning. Based on the exposed considerations, a generic architecture of intelligent CPS, with embedded ML functional modules in multiple learning loops, in order to evaluate way of use of ML functionality in the context of CPPS/CPS. Similarly to other papers found in literature, due to the (informal) inductive methodology applied, considering that this methodology doesn’t provide an absolute proof in favour of, or against, the hypothesis defined, the paper represents a kind of position paper. The paper is divided into two parts. In the first part a review of argumentation from literature, both in favor of and against the thesis on the human role in future, is presented. In this part a concept of the manufacturing singularity is introduced, as well as an intelligent machine
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CYBER-PHYSICAL系统中的机器学习和制造奇异性——这并不意味着完全自动化,人仍然处于中心:第一部分——制造奇异性和智能机器体系结构
在许多流行的科学论述中,有人认为,人工智能的“大规模”使用,包括机器学习,并通过所谓的通用人工智能(AGI)和人工超智能(ASI)达到“奇点”,将完全将人类排除在决策之外,导致机器对人类的完全统治。就制造系统而言,这意味着将实现智能化和完全自动化(一旦人类被排除在外)。本文提出的假设是,AI/ML的自主能力是有限的,更具体地说,ML算法将无法变得完全自主,因此,人类的角色将是不可或缺的。在这个问题的背景下,本文的作者介绍了制造奇点的概念和面向制造奇点的智能机器架构,认为智能机器将始终依赖于人类,并且在制造方面,人类将保持在网络物理系统(CPS)和I4.0的中心。支持这一论点的方法是归纳的,类似于文献中许多文本中应用的方法,并且基于基于归纳推理的机器学习的计算要求。这一论点得到了几个实验的支持,这些实验证明了人类在机器学习过程中的作用。基于暴露的考虑,提出了一种智能CPS的通用架构,在多个学习循环中嵌入ML功能模块,以评估在CPPS/CPS环境中ML功能的使用方式。与文献中发现的其他论文类似,由于采用了(非正式)归纳方法,考虑到该方法不能提供支持或反对所定义假设的绝对证据,该论文代表了一种立场论文。本文分为两个部分。在第一部分中,回顾了文献中对未来人类角色的支持和反对。在这一部分中,引入了制造奇异性的概念,以及一个智能机器
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来源期刊
Journal of Machine Engineering
Journal of Machine Engineering Engineering-Industrial and Manufacturing Engineering
CiteScore
2.70
自引率
0.00%
发文量
36
审稿时长
25 weeks
期刊介绍: ournal of Machine Engineering is a scientific journal devoted to current issues of design and manufacturing - aided by innovative computer techniques and state-of-the-art computer systems - of products which meet the demands of the current global market. It favours solutions harmonizing with the up-to-date manufacturing strategies, the quality requirements and the needs of design, planning, scheduling and production process management. The Journal'' s subject matter also covers the design and operation of high efficient, precision, process machines. The Journal is a continuator of Machine Engineering Publisher for five years. The Journal appears quarterly, with a circulation of 100 copies, with each issue devoted entirely to a different topic. The papers are carefully selected and reviewed by distinguished world famous scientists and practitioners. The authors of the publications are eminent specialists from all over the world and Poland. Journal of Machine Engineering provides the best assistance to factories and universities. It enables factories to solve their difficult problems and manufacture good products at a low cost and fast rate. It enables educators to update their teaching and scientists to deepen their knowledge and pursue their research in the right direction.
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