Deep House - datasets, estrangement, and the problem of the new

Matias del Campo
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Abstract

The purpose of this article is to discuss the application of artificial intelligence (AI) in the design of the Deep House project (Fig. 1), an attempt to use estrangement as a method to emancipate a house from a canonical approach to the progressive design of a one-family house project. The main argument in this text is that the results created by Artificial Neural Networks (ANNs), whether in the form of GANs, CNNs, or other networks, generate results that fall into the category of Estranged objects. In this article, I would like to offer a possible definition of what architecture in this plateau of thinking represents and how it differentiates from previous attempts to use estrangement to explain the phenomena observed when working with NNs in architecture design. A potpourri of thoughts that demonstrate the intellectual tradition of exploring estrangement, especially in theater and literature, that ultimately circles back to its implications for architecture, particularly in light of the application of AI.

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Deep House-数据集、隔阂和新问题
本文旨在讨论人工智能(AI)在 "深宅大院"(Deep House)项目(图 1)设计中的应用,该项目试图利用疏远作为一种方法,将房屋从一户人家房屋项目的渐进式设计的典范方法中解放出来。本文的主要论点是,人工神经网络(ANN)所产生的结果,无论是以 GANs、CNNs 还是其他网络的形式,都会产生属于疏远对象范畴的结果。在本文中,我想就这一思维高原中的建筑所代表的含义,以及它与以往试图用疏远来解释在建筑设计中使用 NNs 时所观察到的现象的不同之处,提供一个可能的定义。这些思考展现了探索疏离感的思想传统,尤其是在戏剧和文学中,最终又回到了它对建筑的影响,尤其是在人工智能的应用方面。
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