Golden generation generator: visualization, reproduction, and closure of structural biases in recent architectural production in Chile, through machine learning

dc.contributor.authorPortal Carrasco, Fernando Andrés.
dc.date.accessioned2024-09-03T19:12:30Z
dc.date.available2024-09-03T19:12:30Z
dc.date.issued2022
dc.description.abstractDeconstruction questions not only the solidity of structures to detect their weakest points but also whether what we understand by structure is actually structural. If we ask, for example, what is structural in a tradition? we can observe – as this research does – that the structure is based on the reiteration of images. But when processing this repetition ad infinitum with artificial intelligence tools, the structural failure appears: an architectural image as disturbing as those that evoke deconstruction.
dc.facultadFacultad de Arquitectura, Animación, Diseño y Construcción
dc.format.extent10 páginas
dc.format.extent3.766Mb
dc.format.mimetypePDF
dc.identifier.citationARQ, 2022(112), 10 p.
dc.identifier.doi10.4067/S0717-69962022000300128
dc.identifier.issn0716-0852
dc.identifier.urihttp://repositorio.udla.cl/xmlui/handle/udla/1228
dc.identifier.urihttps://edicionesarq.com/Revista-ARQ
dc.language.isospa
dc.publisherPontificia Universidad Católica de Chile
dc.sourceARQ
dc.subject.lcshArquitectura
dc.titleGolden generation generator: visualization, reproduction, and closure of structural biases in recent architectural production in Chile, through machine learning
dc.title.alternativeGolden Generation Generator. Visualización, reproducción y clausura de sesgos estructurales en la producción arquitectónica reciente en Chile, a través del aprendizaje maquínico
dc.typeArtículo
dc.udla.catalogadorCBM
dc.udla.indexScopus

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