A Practical Investigation of the Accuracy of Large Language Models in Various Industrial Application Scenarios

Large language models have revolutionized natural language processing, facilitating a wide range of industrial applications. However, their precision and reliability in executing specific tasks across various industries remain incompletely understood. This study investigates the performance of these models across eight industrial scenarios, including code generation, safety monitoring, industrial prototype design, industrial knowledge inquiry, etc. By assessing their accuracy in these domains, the research highlights their practical utility, inherent limitations, and pinpoints areas for enhancement to optimize their deployment in industrial settings.