The ongoing adoption of increasingly complex forms of synthetic intelligence in all facets of contemporary life requires a rethinking of human-AI collaboration within the design process.  This workshop will utilize a series of software platforms to explore the generative and transformative potentials of programming models including convolutional neural networks and model based intelligent agents on the architectural design process.  Specifically, we will explore how these techniques can be linked with contemporary methods for scanning the physical realm into the digital and it’s redeployment into physical though digital fabrication techniques. 

At stake will be a rethinking of architectural aesthetics both in service and in collaboration with non-human intelligences.  The workshop will interrogate both what aesthetic potentials exist through the exploitation of these machines in the production of form, but also question what architectural forms allow for emergent effects and forms of interaction with contemporary social platforms  and interfaces.  The course will explore both how machines can amplify our powers as designers, but also how our designs can amplify the performance of machines. 

Student Work: Students will utilize photogrammetry and structured light sensors to sample 3D physical elements in the built environment.  The first phase of the project will look at transforming these samples into voxel based data structures to explore the designer’s ability to transform, recombine, and alter 3D objects at the granular level.  The second phase will utilize tensorflow generated neural networks to produce digitally augmented versions of these objects through machine vision based AI and augmented reality representations.