It was the fall semester of my thesis year when I walked into the basement of Cal Poly’s spectacular, brutalist architecture building. I was full of excitement. Those who are familiar with the Bachelor of Architecture at Cal Poly know that although it strives to teach design, it also has a heavy focus on preparing students for the technical requirements of the industry. This is why I could not wait to start the architectural theory course which was structured very differently from other classes I had taken. It focused on exploration and critique. The professor had a reputation. He was critical, tough, and direct. I had no problem with that.
Early in the semester, we proposed the topics we wanted to explore. I crafted my abstract and found research and projects to support the current and potential uses of genetic algorithms and evolutionary processes in architecture. Even in 2016, there was a substantial amount of research and applications, and I was able to compile reliable sources. There was also room to expand upon and contribute to the idea.
Genetic algorithms in architecture apply the theories of evolution to design problems. At the most basic level, you have a series of inputs that create a form. You then have criteria that you apply to the output to determine if the output is good or bad. The first run creates a generation based on random inputs. The outputs are evaluated based on your criteria and those that are ‘bad’ are removed. The inputs from those that are ‘good’ are then used to create new, similar inputs, which create the next generation. You repeat this process a specified number of times until you have your surviving options which are closest to your desired criteria. This is a vast over-simplification of the process and writing the software to define your inputs, form, outputs, and criteria is a complex and arduous process. It does, however, allow professionals to do things like optimizing structures to use the least amount of material, laying out tile patterns to minimize waste, and developing ideal office layouts. A computer can run through thousands of options in seconds, creating a curated list of those that meet your criteria the best.
After presenting the topic, I slammed into a brick wall. My professor was a practicing architect, and not someone I would describe as technophobic. However, he had no understanding of what an algorithm was, and he definitely did not want to see its influence in our industry. His feedback was overly critical, cheeky, and, to me, it showed his ignorance. I wish I could say that I researched the topic anyway. That I stood up to his arrogance, defied his audacity, but I did not. I re-wrote my abstract on a typical topic that I do not even recall now because I did not care about it.
The industry kept moving forward. Autodesk first released Project Fractal for beta testing in 2017, months after my class ended, and updated to a new version of the program under the name Project Refinery in 2019. But I did take away something from that class. When someone makes you feel like the outsider in the room, it’s time to find a new room. At BILT North America, I found that new room. I found a community. In Seattle, I was able to learn first-hand from the experts and hear from the creatives. I even had the chance to listen to those who helped to develop Project Refinery.
We all have people in our lives who are criticizers. What keeps our profession moving forward are the brave individuals who dare to dream. Those who dare to draw from ideas that challenge what we do and how we do it. When discovering these ideas for yourself, you may often feel alone, but better times will come. I have found the people who are changing the face of the AEC industry. Whatever you are passionate about, you will find others too.