Using Artificial Intelligence to Shorten Product Development Lifecycle

The primary function of simulation is to enable faster and better decision-making, and both artificial intelligence (AI) and machine learning (ML) are crucial enablers in this process. AI and ML can allow designers to start with a high-level specification, automatically generate numerous design options, and then quickly evaluate which options are the most optimal.

Various AI and ML approaches, including bottom-up methods, top-down methods, reduced-order models (ROMs), and large language models (LLMs), can help solvers perform predictive analysis faster and more accurately. LLMs like ChatGPT can be particularly beneficial in making solvers easier to use. For example, if an engineer wants to run a simulation on an electric car, they would typically have to translate the specifications for different systems, which is time-consuming and requires expertise. With LLMs, anyone can simply describe the desired outcome in natural language, and the simulation will automatically generate a range of solutions, some of which may not have been considered by the human mind.
AI can also improve the way we write code. When a developer needs to upgrade the software, AI can provide the best code snippet to solve the problem. This enhances developer productivity and customer service, as virtual agents can use data from past customer interactions to quickly provide first-level support, allowing experts to focus on more complex issues.