AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ ብ Immanuel Koh

ዲዛይን AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ ብ Immanuel Koh ኣብ ናይ ውድድር ምድብ ጀነረቲቭ፣ ኣልጎሪዝማዊ፣ ፓራሜትሪክን ብ AI ዝተሓገዘ ንድፊን ኣዝዩ ዝኸበረ ተሸላማይ ናይ 2025 ናይ ሓጺን ሽልማት A' Design Award እዩ።

ሓጺንጀነረቲቭ· 2025

AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ

ብ Immanuel Koh

ዓሚል: Immanuel Koh

ኣብ ምድብ ጀነረቲቭ ተሸላማይ ናይ ሓጺን ሽልማት A' Design Award

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ዝተረጋገጸ ተሸላማይ

ንቁጽሪ #170593 ሽልማት ኣረጋግጽ

ሳይት ብጻሕ ኣብ A' Design Award ርአዮ ጋዜጣዊ መግለጺ ባጅ ሽልማት

ሕብርታት

እቲ ዲዛይን

ብዛዕባ AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ

ሲንጋፖር ሰብ-ሰራሕ ከተማ እያ። ብዓቢ ዳታሰት ናይ ሰለስተ-ዓቐናዊ ዲጂታላዊ ሞዴላት ናይ ዓበይቲ ህንጻታት ሲንጋፖር ብዝሰልጠነ፡ እቲ ብፍሉይ ዝተነድፈ AI ሞዴል ብቕርጺ ዝእመንን ብትርጉም ዝሳነን ኣቃውማታት ጥራይ ዘይኮነ ዝፈጥር፡ ኣብ መንጎ ስታንዳርዳዊ ዓይነታት ናይ ዓበይቲ መንበሪ ህንጻታት ከም ጽፍሕታት (ስላብ)፡ ነጥብታትን (ፖይንት) �photopclusterብሎካትን ብምትእትታውን ብምድንዳንን (ኢንተርፖሌሽንን ኤክስትራፖሌሽንን)፡ ሓደስትን ዘገርሙን ስነ-ህንጻዊ ቅርጺታት ክሓስብ ይጅምር።

እቲ ኣፍልጦ

ብዛዕባ ናይ ሓጺን ሽልማት A' Design Award

AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ ናይ ሓጺን ሽልማት A' Design Award ዝዓወተ እዩ፣ ካብ ጽቡቕ ዝተዳለዉ ፍጥረታት ዝጽበዩ ሞያውን ኢንዱስትሪኣውን ጠለባት ንዝመላኡ ጽቡቓት ዲዛይናት ዝወሃብ ክቡር ኣፍልጦ። ዘዓወቱ ሓጺን ዓቢ ክእለት፣ ልዑል ፍሉይነት፣ ክኢላዊ ርድኢትን ፈጠራዊ ዓቕምን ፈጣርዮም የርእዩ። AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ ብብዙሕ ዝተመነየ፣ ዝደነቐን ዝፈተዎን፣ ተግባራውን ሓድሽን ፍጥረት ክኾን ይጽበ። እዚ ዝዓወተ ዲዛይን ናይ ሓጺን ሽልማት A' Design Award ንዝበለጹ ልምድታት ኢንዱስትሪ የጣምር፣ ምስ ፍልጠትን ተውህቦን ዝተኣሳሰሩ ብቑዓት ቴክኒካውያን ባህርያት ድማ ኣለዎ። AI Sampling Singapore ቀንዲ ዕላማ፡ ናይ መንበሪ ስነ-ህንጻ ብጥንቃቐኡ ይኽበር፣ ንዓለም ዝሓሸ ቦታ ክትኸውን ዝሕግዙ ምምሕያሻት መዓርግ ህይወት ንምቕራብ ድማ ዝተዳለወ እዩ።

ድሕሪ እቲ ዲዛይን

ናይ ፕረስ ኪት

ክረዲትታት፣ ኣባላት ጋንታን ቴክኒካዊ ዝርዝራትን ብዲዛይነር ዝቐረቡ።

ፍሉያት ባህርያት: 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.
ዓቐንን ማዕሸግን: 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.
መለለዪታት: AI
ናይ ምፍራይ ቴክኖሎጂ: 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.
ናይ ዲዛይን ብድሆ: 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.
ምርምር: 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.
ምንጪ ሓሳብ: 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.
ናይ ፕሮጀክት ግዜ: 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.
ናይ ስርሒት ፍሰት: This is a digital AI x Architecture generative research project, while the dataset was digitally collected from existing physical buildings in Singapore.
ፓተንታት: Currently no patent.
ኣባላት ጋንታ: Artificial-Architecture
ናይ ስእሊ ክረዲት: All credits: Artificial-Architecture