AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar by Immanuel Koh

AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar by Immanuel Koh is a highly esteemed winner of the very prestigious 2025 Premju A' Design Award tal-Ħadid in Disinn Ġenerattiv, Algoritmiku, Parametriku u Assistit mill-AI Competition Category.

ĦadidĠenerattiv· 2025

AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar

by Immanuel Koh

Client: Immanuel Koh

Premju A' Design Award tal-Ħadid Winner in Ġenerattiv Category

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Colors

The Design

About AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar

Test tal-Ktieb: Singapor hija belt artifiċjali. Imħarreġ b'sett ta' data kbir ta' mudelli diġitali 3D ta' binjiet għoljin li jinsabu f'Singapor, il-mudell tal-IA ddisinjat apposta jiġġenera mhux biss konfigurazzjonijiet formalment plawsibbli u semantikament koerenti, iżda jibda wkoll jimmaġina forom arkitettoniċi ġodda u stramba, billi jinterpola u jestrapola fost it-tipoloġiji standard tad-djar għoljin bħall-blokok tat-tip slab, point, u cluster.

The Recognition

About the Premju A' Design Award tal-Ħadid

AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar huwa rebbieħ tal-Premju A' Design Award tal-Ħadid, rikonoxximent prestiġjuż mogħti lil disinji tajbin li jissodisfaw ir-rekwiżiti professjonali u industrijali mistennija minn ħolqien imfassal tajjeb. Ir-rebbieħa tal-Ħadid juru l-ħila kbira, l-ispeċjalizzazzjoni għolja, il-fehim espert u l-kapaċità kreattiva tal-ħallieqa tagħhom. Huwa mistenni li AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar ikun ħolqien imqabbar ħafna, mammirat u maħbub li huwa prattiku u innovattiv. Dan id-disinn rebbieħ tal-Ħadid jintegra l-aħjar prattiki tal-industrija u għandu karatteristiċi tekniċi kompetenti marbuta mal-għarfien u t-talent. AI Sampling Singapore Funzjoni Primarja: Arkitettura tad-Djar huwa rispettat għall-eżattezza tiegħu u mfassal biex itejjeb il-kwalità tal-ħajja u jgħin jagħmel id-dinja post aħjar.

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