Local Intelligence: Time To Learn From Ai
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis Ltd.
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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.
Description
Keywords
Architecture To Music, Generative Adversarial Networks, Local Intelligence, Localness, Music To Architecture, Pix2Pix
Fields of Science
Citation
WoS Q
N/A
Scopus Q
Q1

OpenCitations Citation Count
N/A
Source
Architectural Science Review
Volume
68
Issue
1
Start Page
13
End Page
28
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Citations
Scopus : 1
Captures
Mendeley Readers : 12
SCOPUS™ Citations
1
checked on Mar 19, 2026
Web of Science™ Citations
2
checked on Mar 19, 2026
Page Views
8
checked on Mar 19, 2026
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