AI Sampling Singapore Architecture résidentielle by Immanuel Koh

AI Sampling Singapore Architecture résidentielle by Immanuel Koh is a highly esteemed winner of the very prestigious 2025 A' Design Award de Fer in Génératif Competition Category.

FerGénératif· 2025

AI Sampling Singapore Architecture résidentielle

by Immanuel Koh

Client: Immanuel Koh

A' Design Award de Fer Winner in Génératif Category

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The Design

About AI Sampling Singapore Architecture résidentielle

Singapour est une ville artificielle. Entraîné avec un vaste ensemble de données de modèles numériques 3D de tours présentes à Singapour, le modèle d'IA conçu sur mesure génère non seulement des configurations formellement plausibles et sémantiquement cohérentes, mais commence également à imaginer des formes architecturales inédites et troublantes, en interpolant et en extrapolant parmi les typologies standard de logements en hauteur telles que les barres, les tours ponctuelles et les blocs groupés.

The Recognition

About the A' Design Award de Fer

AI Sampling Singapore Architecture résidentielle est lauréat de l'A' Design Award de Fer, une reconnaissance prestigieuse décernée à de bons designs qui répondent aux exigences professionnelles et industrielles attendues de créations bien conçues. Les lauréats Fer démontrent la grande compétence, la haute spécialisation, la compréhension experte et la capacité créative de leurs créateurs. AI Sampling Singapore Architecture résidentielle est censé être une création très estimée, admirée et chérie, pratique et innovante. Ce design lauréat de l'A' Design Award de Fer intègre les meilleures pratiques de l'industrie et présente des caractéristiques techniques compétentes associées à un savoir-faire et à du talent. AI Sampling Singapore Architecture résidentielle est respecté pour sa rigueur et est conçu pour apporter des améliorations de la qualité de vie qui contribuent à faire du monde un monde meilleur.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

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.
Team Members: Artificial-Architecture
Image Credits: All credits: Artificial-Architecture