Local Intelligence: Time To Learn From Ai
| dc.contributor.author | Başarır, Lale | |
| dc.contributor.author | Çiçek, S. | |
| dc.contributor.author | Koç, M. | |
| dc.date.accessioned | 2024-05-04T14:17:55Z | |
| dc.date.available | 2024-05-04T14:17:55Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | AI research in architecture is flourishing, and there are plausible and praiseworthy experiments using generative models. These experiments could result in intelligence that uses architectural knowledge and opens new learning opportunities, although guidance is still required in this area. With the Local Intelligence (LI) framework, we hypothesize a web of distributed networks to connect different forms of knowledge linked with architectural context. We assume that the tacit knowledge of vernacular architecture corresponds to the implicit knowledge of folklore music when the anonymous designer and the user are the same- the local people. With a multimodal AI model, we call ‘music2architecture’ – ‘architecture2music’, we argue that sharing the same locality/localness may lead to the emergence of a typical, previously hidden pattern (of wisdom) that we can learn from. © 2024 Informa UK Limited, trading as Taylor & Francis Group. | en_US |
| dc.identifier.doi | 10.1080/00038628.2024.2333547 | |
| dc.identifier.issn | 0003-8628 | |
| dc.identifier.issn | 1758-9622 | |
| dc.identifier.scopus | 2-s2.0-105001955062 | |
| dc.identifier.uri | https://doi.org/10.1080/00038628.2024.2333547 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/5296 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor and Francis Ltd. | en_US |
| dc.relation.ispartof | Architectural Science Review | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Architecture To Music | en_US |
| dc.subject | Generative Adversarial Networks | en_US |
| dc.subject | Local Intelligence | en_US |
| dc.subject | Localness | en_US |
| dc.subject | Music To Architecture | en_US |
| dc.subject | Pix2Pix | en_US |
| dc.title | Local Intelligence: Time To Learn From Ai | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Başarır, Lale | |
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| gdc.coar.access | metadata only access | |
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| gdc.description.department | İzmir Ekonomi Üniversitesi | en_US |
| gdc.description.departmenttemp | Başarır L., Izmır University of Economics, Izmir, Architecture, Turkey; Çiçek S., Architectural Design Computing, Istanbul Technical University, Istanbul, Turkey; Koç M., Architectural Design Computing, Istanbul Technical University, Istanbul, Turkey | en_US |
| gdc.description.endpage | 28 | en_US |
| gdc.description.issue | 1 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q1 | |
| gdc.description.startpage | 13 | en_US |
| gdc.description.volume | 68 | en_US |
| gdc.description.woscitationindex | Arts & Humanities Citation Index | |
| gdc.description.wosquality | N/A | |
| gdc.identifier.openalex | W4393333797 | |
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| gdc.virtual.author | Başarır, Lale | |
| gdc.virtual.author | Çiçek, Selen | |
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