Abstract: The subject matter described herein includes methods, systems, and computer program products for AI tagging of airline fault codes. According to one method, a transformer-based natural language processing (NLP) artificial intelligence (AI) model trained on a dataset is provided. The training dataset includes a plurality of text strings tagged with at least one associated air transport association (ATA) code. The trained AI model then receives an untagged text string as input and automatically tags the text string with an ATA code.

Abstract: An embodiment of a semiconductor package apparatus may include technology to test a target query for one or more similarity metrics over a range of parameters for one or more sets of sequence related information, a multi-domain sequence model, and one or more training routines, select a set of parameters based on a result of the test, and automatically configure the multi-domain sequence model to adapt to one or more of respective data sets, respective prediction tasks, and respective recommendation tasks based on the selected parameters. Other embodiments are disclosed and claimed.