AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen sɣur Immanuel Koh

AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen sɣur Immanuel Koh d anerbaz yettwaqadren meqqren n 2025 Tarbaḥt A' Design Award n Uzzal deg Taggayt n Tnaflit n Afeṣṣel Asniɣes, Alguritman, Aparametran d Win Yettwallalen s AI.

UzzalAfeṣṣel Asniɣes· 2025

AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen

sɣur Immanuel Koh

Amsaɣ: Immanuel Koh

Anerbaz n Tarbaḥt A' Design Award n Uzzal deg Taggayt n Afeṣṣel Asniɣes

60,960

Anerbaz n Urraz Yettwasenqden

Senqed Addad n Urraz i #170593

Rzu ɣer usmel Wali deg A' Design Award Tabḍert n tɣamsa Tanecḍa n wammud

Initen

Afeṣṣel

Ɣef AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen

Aḍris n Udlis: Singapur d tamdint tafelsufant. S uselmed s tɣbula meqqren n iɣawasen imḍinen 3D n yibniyen ɛlayen i d-nettaf di Singapur, talɣa n AI yettwaxedmen s wudem axataṛ ur d-tessufuɣ ara kan iɣewwaṛen yelhan s talɣa yerna ddukklen s wanamek, maca tebda daɣen tett-banuy talɣiwin n tsuddest tijḍidin d tiɣewwaɣanin, tessemtawa tessemɣur gar wanawen iqliqalen n yixxamen ɛlayen am yibloken iblaḍen, ibloken n tneqqiḍt, akked yibloken yedduklen.

Asmekti

Ɣef Tarbaḥt A' Design Award n Uzzal

AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen d amerbaḥ n Tarbaḥt A' Design Award n Uzzal, tagmat i yisnulfa yelhan i yemmalen ayen i d-ttrajun yimdanen seg yisnulfa yelhan. Imerbaḥen n Uzzal ttbanen d tmusni, tmahilt d tazmert n yimahilen-nsen. AI Sampling Singapore Tawuri Tagejdant: Tasuddest n Yixxamen ad yili d asnulfu yettwaɛezzen, yelhan, amaynut. Isnulfa-a ttwaɛezzen imi ɛawnen deg tudert, rran ddunit ugar n lxir.

Deffir n ufeṣṣel

Tagrurt n tɣamsa

Ismawen n terbaɛt, iferdisen itiknikanen akked telɣut i d-yefka umeṣṣufeɣ.

Taɣara Tasuft: Is it possible to sample at scale and at high-resolution every single building ever built in a country? If so, can such a dataset be used to train an AI model in generating new yet locally compliant buildings without any explicit regulatory control inputs? The project explores the design agency of deep generative neural networks in learning three-dimensional exteriority and interiority with a redesigned 3D generative adversarial network (3D-GAN) AI model. Winner of WAFX2024, IDA2024 and BLT2024.
Tigejdiwin & Akemmus: This is a digital AI x Architecture project. Each generated output is a new high-rise high-density residential public housing of up to 30 floors.
Tibzimin: AI
Tasnakta n Ufares: A custom generative AI model was trained from scratch using proprietary code base and dataset. Specifically, a 3D generative adversarial network (3D-GAN) AI model was trained to learn semantic and spatial configuration of high-rise high-density residential public housing in Singapore.
Asewḥel n Usnulfu: The non-existence of 3D models and their corresponding floor plans was the first challenge. New workflow and tools had to be developed to not only collect (i.e., digitally and physically), but create (annotate) and curate (i.e., exploratory data analysis) such high quality dataset to train an AI model from scratch. Technically difficult due to the scalability of similar CAD representation which was overcome via a novel AI latent representation of 3D.
Anadi: A custom generative AI model was trained from scratch using proprietary code base and dataset. Specifically, a 3D generative adversarial network (3D-GAN) AI model was trained to learn semantic and spatial configuration of high-rise high-density residential public housing in Singapore.
Aseḥbiber: Singapore is an artificial city! Trained with a large dataset of 3D digital models of high-rise buildings found in Singapore, the custom-designed AI model generates not only formally plausible and semantically coherent configurations, but begins to also imagine novel and uncanny architectural forms, interpolating and extrapolating among standard high-rise housing typologies such as the slab, point, and cluster blocks. Project exhibited at Venice Architecture Biennale and Singapore's Arts House.
Tanzagt n Usenfar: This is an on-going and longer-term AI x Architecture research being conducted at the university design lab since 2021. It was however only published much later as an official architectural design award entry from 2024 onwards.
Tanila n Umahil: This is a digital AI x Architecture generative research project, while the dataset was digitally collected from existing physical buildings in Singapore.
Ibrivan: Currently no patent.
Igmamen n Terbaɛt: Artificial-Architecture
Imsuren n Tugniwin: All credits: Artificial-Architecture