## 5 Opportunities, Challenges, and Future Developments of VPL-Based Design
### VPL Design--Future Developments
#### 5.3.3 Application of Artificial Intelligence in Engineering Design  
In recent years, certain software producers and, more generally, companies that develop IT technologies and products, have stepped up their efforts to develop and disseminate the technology commonly known as artificial intelligence (AI). In fact, AI is already being used in everyday life, often without people realizing it. Unlocking a smartphone with a fingerprint or using facial or iris scanning as a unique way to secure devices seems imperfect because an AI-based application that can generate a so-called universal fingerprint was developed fairly quickly. In the next few years, AI will become increasingly involved in our lives, trying to relieve us of many activities that require more or less intellectual effort.  
So why not use AI in design? Work in this area has been going on for some time, and one of the results is the development of generative design tools for engineers. In this case, AI does not take the work out of our hands but allows us to perform work that is impossible to do manually. Just as it is impossible to compare the computing power of a well-equipped computer with the capabilities of cloud computing, it makes no sense to compare computing power in terms of generating variants of situations that can be obtained using generative design. Why not go further and try to develop intelligent programming tools that would optimize the design process to some extent? Tools that have been used for some time, such as genetic algorithms used to optimize various structural designs [46; 47], and others [48], could be applied here. By applying the appropriate criteria, the engineer would obtain a product that would be tailored to his needs. This may seem like too big a leap in terms of the development of programming tools, which are currently not very advanced. In reality, it is simply a matter of developing software for the existing environment. Obviously, this requires much work, but given the opportunities it offers, it should happen sooner or later.  
An example of an AI application in the areas discussed above is the Python code generated by ChatGPT to design a roof truss, as shown in Figure 27. Due to current limitations, this code is intended to be executed within the Dynamo environment.  
Figure 27: Python code generated by AI to design a roof truss.  
It creates a roof truss as a structural framing element in Revit, based on the specified span, pitch, and depth parameters. It sets various properties of the truss, such as depth, pitch, span, family, and type, and assigns it to a specific level. Finally, the code outputs the created truss element. This code assumes to have the necessary Revit and Dynamo packages installed and referenced in the Dynamo environment.  
The possibilities offered by software manufacturers for some time now give rise to the hope that, by improving the tools offered and expanding their areas of application, it will be possible to use this technique in everyday applications, such as optimizing the weight of a designed structure.