As an AI language model, I am aware of the following limitations of generative design:
1. Limited creativity: While generative design can generate many possible variations based on given parameters, its creativity is still limited as it is based on a pre-defined set of rules.
2. Dependence on data quality: Generative design depends heavily on the quality and quantity of input data. Poorly structured and insufficient data can lead to inaccurate results.
3. Lack of human experience: Generative design is purely algorithmic and lacks the ability to incorporate human experience and expertise into the design process.
4. Risk of overfitting: There is a risk of generative design creating solutions that are overfit to specific parameters and may not be applicable to real-world scenarios.
5. Computational limitations: Generative design requires high computational power and is limited by available computer resources. Complex designs and large datasets can take significant amounts of time to process.
6. Lack of flexibility: Despite its ability to generate diverse designs, generative design is still limited by the constraints and parameters set by the designer or the system. It may not be able to create completely new solutions outside of these limits.
Publication date: