Learning as a Cloud Service - will create a distributed learning layer, which is a mechanism for working with data no matter where it is stored, through desktop, mobile and other devices.

Resource Repository Network - will create a resource graph of learning/training resources data from multiple sources and multiple formats including live and dynamic data such as workplace data, plant instrumentation, or market information.

Personal Learning Record - will define how we represent, capture, and leverage user activity, including ratings, test results, performance measures, and the like, in a distributed learning and work environment.

Automated Competence Development and Recognition - whereas existing recommender systems depend on manually defined metrics and taxonomies, this system will detect new and emerging competences and automatically assess employee performance.

Personal Learning Assistant - will develop an integrated learning appliance, a mechanism for looking up or finding references or resources inside other programs or environments.