Intelligently combining design features of different designs can yield radically new functional designs.
Using Deep Learning to Generate Conceptual Design
Collaborators: Imdat As + Prithwish Basu
Project Duration: Jan 2018 - May 2018
Funding: DARPA (Defense Advanced Research Projects Agency) Grant
Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this project we worked on an alternative graph-based machine learning system that deals with three-dimensional space, which is more structured and combinatorial than images, text or voice. Specifically, we explored a function-driven deep learning approach to generate conceptual design. We trained and used deep neural networks to evaluate existing designs encoded as graphs, extract significant building blocks as subgraphs and merge them into new compositions. Finally, we explored the application of generative adversarial networks to generate entirely new and unique designs.
[Upcoming] Imdat As and Prithwish Basu, The Routledge Companion to Artificial Intelligence in Architecture, Taylor & Francis, scheduled for publication Jan 2021.
“Composing Frankensteins: Data-driven design assemblies through graph-based deep neural networks,” (with Prithwish Basu and Siddarth Pal) Computer Composition: Design after Machine Learning, 107th ACSA Conference, Carnegie Mellon University, Pittsburgh, PA, March 28-30, 2019.
“Artificial intelligence in architecture: Generating conceptual design via deep learning,” (with Prithwish Basu and Siddarth Pal), International Journal of Architectural Computing (IJAC), Vol. 16, Issue 4, 2018: 306-327.
Kirk, Mimi, “Will the Advent of Artificial Intelligence Affect Small Firms,” Architect Magazine, (Publication of the American Institute of Architects - AIA), Washington, DC, February 2019.
Crosbie, Michael, “Doom or Bloom: What will Artificial Intelligence Mean for Architecture,” CommonEdge.org (also published on ArchDaily.com), 2018.
PRESENTATIONS, PANELS AND LECTURES:
107th ACSA Conference, “Composing Frankensteins: Data-driven design assemblies through graph-based deep neural networks,” Computer Composition: Design after Machine Learning, Carnegie Mellon University, Pittsburgh, PA, March 28-30, 2019.
Hochschule Wismar, University of Applied Sciences, Technology, Business and Design, “24 hours Berlin City West,” International Workshop on the Future City in Berlin, Germany, March 16-24, 2019.
Bilkent University, “The Future is History: Architecture in the Age of Artificial Intelligence,” Ankara, Turkey, 2018.