[{"name":"S6-240038","title":"AI\/ML model lifecycle management","source":"TNO","contact":"Nassima Toumi","contact-id":97967,"tdoctype":"pCR","for":"Approval","abstract":"This contribution provides a new solution to support AI\/ML model lifecycle, where the AI\/ML Enablement capability can trigger model update upon detecting model performance degradation. To optimize the (re-) training process, a base model can be selected for Transfer Learning. The solution also considers relationships between models (e.g. Transfer Learning, or training using the same input data) to update additional models as well.","secretary_remarks":"","agenda_item_sort_order":34,"ainumber":"8.3","ainame":"FS_AIMLAPP - Study on application layer support for AI\/ML services","tdoc_agenda_sort_order":0,"status":"revised","reservation_date":"2024-12-02 15:56:13","uploaded":"2024-02-13 10:58:20","revisionof":"","revisedto":"S6-240648","release":"Rel-19","crspec":"23.700-82","crspecversion":"0.2.0","workitem":[{"winame":"FS_AIMLAPP"}],"crnumber":"","crrevision":"","crcategory":"","tsg_crp":"","lsreplyto":"","lsto":"","Cc":"","lsoriginalls":"","lsreply":"","link":"https:\/\/www.3gpp.org\/ftp\/tsg_sa\/WG6_MissionCritical\/TSGS6_059_Athens\/Docs\/S6-240038.zip","group":"S6","meeting":"S6-59","year":2024,"uicc_affected":"","me_affected":"","ran_affected":"","cn_affected":"","clauses_affected":"","crsinpack":null,"crsinpacknumber":0}]