Imaginary Maps

Imaginary Maps – A posthuman urban design method based on Neural Style Transfer


Matias del Campo, Sandra Manninger, Alexandra Carlson


Artificial Intelligence, Design, Architecture, Machine Learning, Posthumanism, Urban Planning, Generative design, Utopia, Artificial Neural Networks, Computational Design, Deep Learning, Hallucinations, Datamining, Generative Architectural Design, Convolutional Neural Networks, Generative Adversarial Networks, Image style transfer, Machine Hallucination 


The main aim of this paper is to demonstrate and interrogate a design technique based on deep learning. The discussion includes aspects of machine learning, 2D to 2D style transfers, and generative adversarial processes. The paper examines the meaning of agency in a world where decision-making processes are defined by human/machine collaborations and their relationship to aspects of a Posthuman design ecology. Taking cues from the language used by experts in AI such as Hallucinations, Dreaming, Style Transfer, and Vision, the paper strives to clarify the position and role of Artificial Intelligence in the discipline of urban design.

Fig.1: Results of 2D to 2D Style transfers based on Nolli plans and an image of the Moon: aspects of Estrangement and Defamiliarization profoundly speak in those results about a design ecology in a Posthuman era.

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