dc.contributor.author | Kumpulainen, Samu | |
dc.contributor.author | Terziyan, Vagan | |
dc.contributor.editor | Longo, Francesco | |
dc.contributor.editor | Affenzeller, Michael | |
dc.contributor.editor | Padovano, Antonio | |
dc.date.accessioned | 2022-03-21T11:07:18Z | |
dc.date.available | 2022-03-21T11:07:18Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Kumpulainen, S., & Terziyan, V. (2022). Artificial General Intelligence vs. Industry 4.0 : Do They Need Each Other?. In F. Longo, M. Affenzeller, & A. Padovano (Eds.), <i>3rd International Conference on Industry 4.0 and Smart Manufacturing</i> (200, pp. 140-150). Elsevier. Procedia Computer Science. <a href="https://doi.org/10.1016/j.procs.2022.01.213" target="_blank">https://doi.org/10.1016/j.procs.2022.01.213</a> | |
dc.identifier.other | CONVID_104552861 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/80271 | |
dc.description.abstract | Artificial Intelligence (AI) is known to be a driving force behind the Industry 4.0. Nowadays the current hype on development and industrial adoption of the AI systems is mostly associated with the deep learning, i.e., with the abilities of the AI to perform various specific cognitive activities better than humans do. However, what about the Artificial General Intelligence (AGI), associated with the generic ability of a machine to perform consciously any task that a human can? Do we have many samples of the AGI research adopted by Industry 4.0 and used for smart manufacturing? In this paper, we report the systematic mapping study regarding the AGI-related papers (published during the five-year period) to find out whether AGI is giving up its positions within AI as an attractive tool to address the industry needs. We show what the major concerns of the AGI academic community are nowadays and how the AGI findings have been already or could be potentially applied within the Industry 4.0. We have discovered that the gap between the AGI studies and the industrial needs is still high and even has some indications to grow. However, some AGI-related findings have potential to make real value in smart manufacturing.
https://ai.it.jyu.fi/ISM-2021-AGI.pptx | en |
dc.format.extent | 1918 | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.relation.ispartof | 3rd International Conference on Industry 4.0 and Smart Manufacturing | |
dc.relation.ispartofseries | Procedia Computer Science | |
dc.rights | CC BY-NC-ND 4.0 | |
dc.subject.other | Artificial general intelligence | |
dc.subject.other | Industry 4.0 | |
dc.subject.other | systematic mapping study | |
dc.subject.other | Google distance | |
dc.title | Artificial General Intelligence vs. Industry 4.0 : Do They Need Each Other? | |
dc.type | conference paper | |
dc.identifier.urn | URN:NBN:fi:jyu-202203211969 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.contributor.oppiaine | Collective Intelligence | fi |
dc.contributor.oppiaine | Tekniikka | fi |
dc.contributor.oppiaine | Collective Intelligence | en |
dc.contributor.oppiaine | Engineering | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 140-150 | |
dc.relation.issn | 1877-0509 | |
dc.relation.volume | 200 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2022 The Authors. Published by Elsevier B.V. | |
dc.rights.accesslevel | openAccess | fi |
dc.type.publication | conferenceObject | |
dc.relation.conference | International Conference on Industry 4.0 and Smart Manufacturing | |
dc.subject.yso | tekoäly | |
dc.subject.yso | teollisuus | |
dc.subject.yso | älytekniikka | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2616 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p998 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p27260 | |
dc.rights.url | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.relation.doi | 10.1016/j.procs.2022.01.213 | |
dc.type.okm | A4 | |