Using Large Language Models for Flight Test Data Analysis

This brief will explore the potential benefits of using large language models (LLMs) for flight test data analysis. It will discuss how LLMs can be used to process and interpret the vast amount of information present in different types of flight test data, and how this can lead to more effective decision-making, improved safety assessments, and optimized aircraft performance. LLMs have the potential to revolutionize the field of flight test data analysis by providing a more efficient and effective way to process and interpret large datasets. However, there are also some challenges that need to be addressed, such as the need for accurate and relevant datasets. Ongoing research and advancements in LLM technology will likely continue to enhance their capabilities for complex data analysis tasks in aviation and other domains. Offline LLMs can be used to handle CUI data, which is a type of sensitive information that requires special handling. This can be done by training the LLM on a dataset of CUI data that has been scrubbed of sensitive information. The brief will also discuss the future of LLMs in the field of flight test data analysis.