AI Sampling Singapore Boligarkitektur by Immanuel Koh

AI Sampling Singapore Boligarkitektur by Immanuel Koh is a highly esteemed winner of the very prestigious 2025 A' Design Award i Jern in Generativt, Algoritmisk, Parametrisk og KI-assistert Design Competition Category.

JernGenerativt· 2025

AI Sampling Singapore Boligarkitektur

by Immanuel Koh

Client: Immanuel Koh

A' Design Award i Jern Winner in Generativt Category

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Verified Award Winner

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The Design

About AI Sampling Singapore Boligarkitektur

Singapore er en kunstig by. Trent med et stort datasett av 3D digitale modeller av høyhus funnet i Singapore, genererer den spesialdesignede AI-modellen ikke bare formelt plausible og semantisk sammenhengende konfigurasjoner, men begynner også å forestille seg nye og uhyggelige arkitektoniske former, ved å interpolere og ekstrapolere blant standard typologier for høyhusboliger som plate-, punkt- og klyngeblokker.

The Recognition

About the A' Design Award i Jern

AI Sampling Singapore Boligarkitektur er vinner av A' Design Award i Jern, en prestisjefylt anerkjennelse som tildeles gode design som oppfyller de profesjonelle og industrielle kravene man forventer av veldesignede skaperverk. Jernvinnere viser stor dyktighet, høy spesialisering, ekspertforståelse og kreativ kapasitet hos skaperne. AI Sampling Singapore Boligarkitektur forventes å være et høyt ansett, beundret og verdsatt skaperverk som er praktisk og nyskapende. Dette designet, som har vunnet A' Design Award i Jern, integrerer bransjens beste praksis og har kompetente tekniske egenskaper knyttet til kunnskap og talent. AI Sampling Singapore Boligarkitektur respekteres for sin grundighet og er utformet for å gi forbedringer i livskvalitet som bidrar til å gjøre verden til et bedre sted.

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