In July 2024, as the revenue from empowered amateurs disappoints investors and the hype subsides, discussions around AI will quickly become outdated. AI’s role as a tool, however, will persist. The current “outside in” brute force methods will give way to an “inside out” approach. Smart models will interact directly with surfaces and skeletons rather than pixels and meshes. This shift cannot rely on scraping existing data but will require industry-specific development and domain expertise, such as FBX animations, or Nurbs creation methods.
To begin, there’s a need for a designer-accessible parametric model wrapped in a UI. Here’s a practical example of such an approach applied to surface creation for helmets:
( 24" touchscreen interface on the top third of the screen, CAD window bottom 2/3, 10X speed)
The underlying concept of this project, HST, focuses on helmet shapes using single-span surfaces. These surfaces are challenging to parameterize and typically require manual control point manipulation to achieve desired forms. Single-span surfaces excel in aesthetics and serve as foundational elements for functional and stylistic components throughout the design process.
Parametric models enable extensive and complex manipulations with strategic inputs. These inputs can be trained into specific AI models, such as a custom ChatGPT model.
Training involves designers describing their intent and monitoring changes within a 3D model, specifically adjustments in driving parameters.
Usage entails requesting modifications through verbal or image input, with the AI API delivering adjusted parametric settings and an instantaneous rebuild of the 3D model.
This approach marks a step towards leveraging AI for streamlined and intuitive design processes, tailored to specific industrial needs and creative workflows.
HST implements a forward-thinking approach to integrating parametric modeling with AI capabilities, specifically tailored for the demands of helmet design. By focusing on single-span surfaces and leveraging smart models, we aim to enhance both aesthetic quality and functional efficiency in the design process.
Thoughts and feedback on this approach? How do you see AI evolving in the realm of CAD and design? Are there specific challenges or features you believe should be prioritized?