Neural Tectonics

Abstract The article interprets tectonics in the age of artificial intelligence with the concept of ‘Neural Tectonics.’ In tectonics, poetics are presented through the assembly of materials. In contrast, neural tectonics is the synthetic poetics presented through the structure of deep neural networks and the semantics of training datasets. Around the concepts of artificial/authentic and artifacts, the article touches on issues important to both architecture and computing, including representation and geometrical projection space/latent space, and elaborates this process with the work Neural Artefact Black. Neural Tectonics seeks a kind of AI-native architecture, which is based on the generative logic of AI rather than the imitation and consumption of architectural styles. It promotes a reflection on ‘deep artificiality.’