Machinic Interpolation targets the need to integrate lateral thinking strategies in digital design tools. Many of the tools used by architects to design, conceptualize and experiment have entered into the discipline from fields such as engineering, manufacturing or animation. As a result, values such as optimization, standardization and efficiency have discretely found their way into these tools and have greatly informed and constrained the possible design space.

Within this context, the project proposes a methodology that uses GANs and their properties as an experimentation ground to reevaluate the lateral thinking constraints in architectural tools. Specifically, it uses StyleGAN and explores the ability to access its latent space as part of an architectural design process.

The presented methodology constitutes a 4-step approach that draws from the abilities and properties of this space to design architecture: initializing the virtual environment of points (through training), entering the space (randomly or with an intent), moving through space (through arithmetic operations and interpolations), and finally generating voxelized 3D forms from interpolated images.

By doing this, the project reveals how this series of techniques could lead to unexpected spaces, resulting in creative output beyond what is produced by human capability alone.