AI Sampling Singapore Primärfunktion: Wohnarchitektur by Immanuel Koh

AI Sampling Singapore Primärfunktion: Wohnarchitektur by Immanuel Koh is a highly esteemed winner of the very prestigious 2025 A' Design Award in Eisen in Generatives Design Competition Category.

EisenGenerativ· 2025

AI Sampling Singapore Primärfunktion: Wohnarchitektur

by Immanuel Koh

Client: Immanuel Koh

A' Design Award in Eisen Winner in Generativ Category

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The Design

About AI Sampling Singapore Primärfunktion: Wohnarchitektur

Buchtext: Singapur ist eine künstliche Stadt. Trainiert mit einem umfangreichen Datensatz aus digitalen 3D-Modellen von Hochhäusern in Singapur, erzeugt das maßgeschneiderte KI-Modell nicht nur formal plausible und semantisch kohärente Konfigurationen, sondern beginnt auch, neuartige und befremdliche architektonische Formen zu imaginieren, indem es zwischen gängigen Hochhaus-Wohntypologien wie Scheiben-, Punkt- und Clusterbauten interpoliert und extrapoliert.

The Recognition

About the A' Design Award in Eisen

AI Sampling Singapore Primärfunktion: Wohnarchitektur ist Gewinner des A' Design Award in Eisen, einer prestigeträchtigen Anerkennung für gute Designs, die die beruflichen und industriellen Anforderungen erfüllen, die an gut gestaltete Schöpfungen gestellt werden. Eisen-Gewinner zeigen großes Können, hohe Spezialisierung, fachkundiges Verständnis und die kreative Kapazität ihrer Schöpfer. Von AI Sampling Singapore Primärfunktion: Wohnarchitektur wird erwartet, dass es eine hochgeschätzte, bewunderte und geliebte Schöpfung ist, die praktisch und innovativ ist. Dieses mit dem A' Design Award in Eisen prämierte Design integriert bewährte Branchenverfahren und weist kompetente technische Merkmale in Verbindung mit Know-how und Talent auf. AI Sampling Singapore Primärfunktion: Wohnarchitektur wird für seine Gründlichkeit geschätzt und ist darauf ausgelegt, Verbesserungen der Lebensqualität zu liefern, die dazu beitragen, die Welt zu einem besseren Ort zu machen.

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