Large language models offer a number of benefits for both automation engineers and enterprise management. For automation engineers, LLMs have the potential to revolutionise the development process by automatically generating and completing code. This speeds up the entire process. In addition, you can even have LLMs create personal tutorials and specifically ask for solutions to problems that arise. From an enterprise management perspective, LLMs promote knowledge transfer within the organisation. They can act as a central knowledge base, storing valuable information and making it available when needed. In addition, LLMs can relieve the pressure on the support team by serving as the first point of contact for customer inquiries.
TwinCAT Chat was developed to integrate LLMs into control engineering, giving users a clear benefit when compared to using ChatGPT traditionally in a web browser, for example. This greatly simplifies the development process, as communication and code exchange are seamlessly integrated. Furthermore, the basic initialisation of the LLM has been tailored specifically to TwinCAT requests. You can thus ask specific questions directly, and don’t have to tell the LLM that you are using TwinCAT first, and that the code examples are expected in Structured Text. In addition, the generated code can be easily transferred, which not only saves developers time, but also prevents the errors that occur when transferring code manually. For efficient interaction with TwinCAT Chat, simple one-click pre-tested requests can be used that are specifically designed to improve the user’s workflow.
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