IJzer Generatief · 2025
AI Sampling Singapore Primaire functie: Woningarchitectuur
by Immanuel Koh
- A' Design Award in IJzer 2025 in Generatief
- CLIENT: Immanuel Koh
- Estimated Number of Design Views: 60,008
- Verification code C83C4A52C0 · Verify this award
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About AI Sampling Singapore Primaire functie: Woningarchitectuur
Boektekst: Singapore is een kunstmatige stad. Getraind met een grote dataset van 3D-digitale modellen van hoogbouw in Singapore, genereert het op maat ontworpen AI-model niet alleen formeel plausibele en semantisch coherente configuraties, maar begint het ook nieuwe en bevreemdende architecturale vormen te verbeelden, waarbij het interpoleert en extrapoleert tussen standaard typologieën van hoogbouwwoningen zoals de slab-, point- en clusterblokken.
About the A' Design Award in IJzer
AI Sampling Singapore Primaire functie: Woningarchitectuur is winnaar van de A' Design Award in IJzer, een prestigieuze erkenning die wordt toegekend aan goede ontwerpen die voldoen aan de professionele en industriële eisen die worden verwacht van goed ontworpen creaties. Winnaars in IJzer tonen grote vaardigheid, hoge specialisatie, deskundig inzicht en het creatieve vermogen van hun makers. AI Sampling Singapore Primaire functie: Woningarchitectuur wordt verwacht een hooggewaardeerde, bewonderde en gekoesterde creatie te zijn die praktisch en innovatief is. Dit ontwerp dat de A' Design Award in IJzer heeft gewonnen, integreert de beste praktijken uit de sector en heeft bekwame technische kenmerken die verbonden zijn met knowhow en talent. AI Sampling Singapore Primaire functie: Woningarchitectuur wordt gerespecteerd om zijn grondigheid en is ontworpen om verbeteringen van de levenskwaliteit te bieden die helpen de wereld een betere plek te maken.
Press Kit
- Unique Properties
- 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.
- Dimensions & Packaging
- 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.
- Tags
- AI
- Production Technology
- 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.
- Design Challenge
- 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.
- Research
- 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.
- Inspiration
- 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.
- Project Duration
- 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.
- Operation Flow
- This is a digital AI x Architecture generative research project, while the dataset was digitally collected from existing physical buildings in Singapore.
- Patents
- Currently no patent.
- Image Credits
- All credits: Artificial-Architecture
