- The application of AttnGAN in Architectural design
- Design Team: Matias del Campo, Sandra Manninger, Yining Yuan, Yanci Chen & Mike Shin
Artificial intelligence as a design driver
In recent years architecture design has entered the field of designing with the aid of artificial intelligence. This project is a pioneering example of the use of artificial intelligence as a driving force of design. Based on pragmatic criteria such as the allover massing of the school, the topographic and environmental qualities of the site, and the programmatic needs, the design team programmed a Machine Learning (ML) algorithm to split and subdivide the larger volumes into chunks and pieces that represent the desired qualities of human scale and intimate spaces. The goal behind the subdivision of the volumes is to achieve a scale that is not intimidating but inviting to students and faculty alike. In addition, the same algorithm provides the basis for the coloration of the design. Color is of crucial importance for the design, it amplifies the atmospheric qualities of the design and provides an additional layer that contributes to the unique identity of this project. The project strives for an architecture that allows students and faculty to identify themselves with the built environment of this school. In contrast to schools in the 20th century, which occasionally strived for a certain extent of anonymity in their architectural expression – following technocratic principles- this project strives for the opposite in that it intentionally serves as a platform for the identity of the community populating this school, from the staff and the faculty to the students occupying this space. The coloration provided by the Machine Learning Algorithm is interpreted in a variety of different ways, which reach from the simple color of patches of the buildings, to the subdivision of the landscaping into patches of various vegetation and ground materials (gravel, grass, sand, concrete, etc.)
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