AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ by Immanuel Koh

AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ by Immanuel Koh is a highly esteemed winner of the very prestigious 2025 A' Design Award ລະດັບເຫຼັກ in ການອອກແບບແບບກຳເນີດ, ອັນກໍຣິທຶມ, ພາຣາເມຕຣິກ ແລະ AI ຊ່ວຍ Competition Category.

ເຫຼັກແບບກຳເນີດ· 2025

AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ

by Immanuel Koh

Client: Immanuel Koh

A' Design Award ລະດັບເຫຼັກ Winner in ແບບກຳເນີດ Category

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The Design

About AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ

ເນື້ອໃນປຶ້ມ: ສິງກະໂປເປັນເມືອງທີ່ສ້າງຂຶ້ນໂດຍມະນຸດ. ດ້ວຍການຝຶກຝົນຈາກຊຸດຂໍ້ມູນຂະໜາດໃຫຍ່ຂອງແບບຈໍາລອງດິຈິຕອລ 3 ມິຕິ ຂອງຕຶກສູງທີ່ພົບເຫັນຢູ່ໃນສິງກະໂປ, ແບບຈໍາລອງ AI ທີ່ອອກແບບສະເພາະ ບໍ່ພຽງແຕ່ສ້າງການຈັດວາງທີ່ມີຮູບແບບເປັນໄປໄດ້ ແລະ ມີຄວາມສອດຄ່ອງທາງຄວາມໝາຍເທົ່ານັ້ນ, ແຕ່ຍັງເລີ່ມຈິນຕະນາການເຖິງຮູບແບບສະຖາປັດຕະຍະກໍາທີ່ແປກໃໝ່ ແລະ ໜ້າປະຫຼາດໃຈ, ໂດຍການແຊກສະຫຼັບ ແລະ ຄາດຄະເນຂະຫຍາຍລະຫວ່າງປະເພດທີ່ຢູ່ອາໄສຕຶກສູງມາດຕະຖານ ເຊັ່ນ: ບລັອກແບບແຜ່ນ, ແບບຈຸດ, ແລະ ແບບກຸ່ມ.

The Recognition

About the A' Design Award ລະດັບເຫຼັກ

AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ ແມ່ນຜູ້ຊະນະ A' Design Award ລະດັບເຫຼັກ ເຊິ່ງເປັນການຍອມຮັບທີ່ມີກຽດສຳລັບການອອກແບບທີ່ດີ ທີ່ຕອບສະໜອງຄວາມຕ້ອງການທາງວິຊາຊີບ ແລະ ອຸດສາຫະກຳທີ່ຄາດຫວັງຈາກຜົນງານທີ່ອອກແບບມາຢ່າງດີ. ຜູ້ຊະນະລະດັບເຫຼັກສະແດງເຖິງທັກສະອັນຍິ່ງໃຫຍ່ ຄວາມຊຳນານສະເພາະສູງ ຄວາມເຂົ້າໃຈຂອງຜູ້ຊ່ຽວຊານ ແລະ ຄວາມສາມາດໃນການສ້າງສັນຂອງຜູ້ສ້າງ. AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ ຖືກຄາດວ່າຈະເປັນຜົນງານທີ່ໄດ້ຮັບການຍົກຍ້ອງສູງ ໜ້າຊົມເຊີຍ ແລະ ເປັນທີ່ຮັກແພງ ທີ່ໃຊ້ງານໄດ້ຈິງ ແລະ ມີນະວັດຕະກຳ. ການອອກແບບທີ່ຊະນະລະດັບເຫຼັກນີ້ລວມວິທີປະຕິບັດທີ່ດີທີ່ສຸດຂອງອຸດສາຫະກຳ ແລະ ມີຄຸນລັກສະນະທາງເຕັກນິກທີ່ມີຄວາມສາມາດ ເຊື່ອມໂຍງກັບຄວາມຮູ້ ແລະ ພອນສະຫວັນ. AI Sampling Singapore ໜ້າທີ່ຫຼັກ: ສະຖາປັດຕະຍະກໍາທີ່ຢູ່ອາໄສ ໄດ້ຮັບການເຄົາລົບສຳລັບຄວາມລະອຽດຮອບຄອບ ແລະ ຖືກອອກແບບເພື່ອປັບປຸງຄຸນນະພາບຊີວິດ ຊ່ວຍເຮັດໃຫ້ໂລກເປັນບ່ອນທີ່ດີຂຶ້ນ.

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