Onur Yüce Gün, Director of Computational Design at New Balance on the 'Shape Of Generative AI'
CDFAM Interview
While it may be fun to prompt Midjourney to synthesize images of otherworldly architecture from mere words, or create hundreds of renders of sneaker concepts with the most fantastic themes in seconds, is it really architecture or design?
The building renders you create with AI imagery are not buildings.
There is no AI architecture.
Or everybody is an AI architect who makes building images.
Feel free to pick one idea over the other one.
Onur Yüce Gün - Director of Computational Design, New Balance
It is easy to get excited about the potential for a new tool, software or algorithm to help unlock infinite human potential in design, it is important to stop and take a breath before diving head first into what may be a very unproductive rabbit hole with no true path to bringing concepts to reality.
In an interview with Onur Yüce Gün - Director of Computational Design, New Balance in preparation for his keynote presentation at CDFAM Berlin on May 7, 2024, we discuss how he and his team take a measured approach to the exploration and adoption of generative AI for design and engineering.
I kept playing with, reading, testing, and implementing.
Everyone should shift focus on the tools that look promising and investigate quickly if that sensation is true. So, I found value in pushing the brake a bit more than the gas as the overall tendency was to accelerate as much as possible.
Once you realize that only a fraction of what is promised can be realized, it makes more sense to keep your foot on the brake and accelerate with the tools and methods you believe in.
As we have seen in the post on AI Driven 'Generative Design' Experiments for Engineering where we explored NVIDIA’s a proof of concept API with Shutterstock called Edify-3D, none of the available Generative AI tools for ‘design’ have connection to the physics of performance or constraints of manufacture. This severely limits the potential of the tools beyond idea generation and concept communication.
As presented today, the generative models look inexhaustible, but they keep yielding the same result repeatedly.
That is not interesting at all, especially in the design context.
Onur goes on to say that the generative tools that have a greater inputs for human interaction are those that yield the best results, once you understand how they work.
The tools that enable more human input proved to be more successful. As in the case of image generation tools, sketch-to-render tools create more tangible and useful results than text-to-image tools.
Those will have longevity in design processes…
…The best way to use a tools is the critical employment of it. To be critical, you need first to know what you are doing and how the tool is doing it.
Read the full article with Onur to learn more about his approach to generativeAI and other transformational computational tools at New Balance.
Don’t miss out on the opportunity to connect in person at CDFAM Berlin where experts from around the world will be presenting their ideas, software tools and research on the adoption of AI in engineering and architecture.
