US Patent Application 17804322. COMPATIBLE AND SECURE SOFTWARE UPGRADES simplified abstract
Contents
COMPATIBLE AND SECURE SOFTWARE UPGRADES
Organization Name
International Business Machines Corporation
Inventor(s)
COMPATIBLE AND SECURE SOFTWARE UPGRADES - A simplified explanation of the abstract
This abstract first appeared for US patent application 17804322 titled 'COMPATIBLE AND SECURE SOFTWARE UPGRADES
Simplified Explanation
- The patent application describes techniques for managing machine learning libraries in a machine learning platform. - The techniques involve creating a table that lists the machine learning libraries used in a deployed machine learning platform instance, along with their current versions. - The table also includes information about available version upgrades for each library, including a security indication and a compatibility indication. - Based on this information, the techniques generate recommendations for upgrading the machine learning libraries. - The recommendations take into account both the security indication, which indicates the level of security provided by the available version upgrade, and the compatibility indication, which indicates how well the available version upgrade will work with the current version of the library. - The goal of these techniques is to simplify the process of managing machine learning libraries and ensure that the platform is using the most secure and compatible versions.
Original Abstract Submitted
Described are techniques for machine learning library management. The techniques include generating a table including a plurality of machine learning libraries and their current versions that are used in a deployed machine learning platform (MLP) instance, a first available version upgrade for a first machine learning library of the plurality of machine learning libraries, a security indication associated with the first available version upgrade relative to a current version implemented by the first machine learning library, and a compatibility indication between the first available version upgrade and the current version of the first machine learning library. The techniques further include generating a recommendation related to upgrading the first machine learning library based on the security indication and the compatibility indication.
