Machine intelligence today: applications, methodology, and technology
| dc.contributor.author | Humm, Bernhard G. | |
| dc.contributor.author | Bense, Hermann | |
| dc.contributor.author | Fuchs, Michael | |
| dc.contributor.author | Gernhardt, Benjamin | |
| dc.contributor.author | Hemmje, Matthias | |
| dc.contributor.author | Hoppe, Thomas | |
| dc.contributor.author | Kaupp, Lukas | |
| dc.contributor.author | Lothary, Sebastian | |
| dc.contributor.author | Schäfer, Kai-Uwe | |
| dc.contributor.author | Thull, Bernhard | |
| dc.contributor.author | Vogel, Tobias | |
| dc.contributor.author | Wenning, Rigo | |
| dc.date.accessioned | 2021-04-14T10:17:51Z | |
| dc.date.available | 2021-04-14T10:17:51Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Machine intelligence, a.k.a. artificial intelligence (AI) is one of the most prominent and relevant technologies today. It is in everyday use in the form of AI applications and has a strong impact on society. This article presents selected results of the 2020 Dagstuhl workshop on applied machine intelligence. Selected AI applications in various domains, namely culture, education, and industrial manufacturing are presented. Current trends, best practices, and recommendations regarding AI methodology and technology are explained. The focus is on ontologies (knowledge-based AI) and machine learning. | de |
| dc.identifier.doi | 10.1007/s00287-021-01343-1 | |
| dc.identifier.pissn | 1432-122X | |
| dc.identifier.uri | http://dx.doi.org/10.1007/s00287-021-01343-1 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/36168 | |
| dc.publisher | Springer | |
| dc.relation.ispartof | Informatik Spektrum: Vol. 44, No. 2 | |
| dc.relation.ispartofseries | Informatik Spektrum | |
| dc.title | Machine intelligence today: applications, methodology, and technology | de |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 114 | |
| gi.citation.startPage | 104 |