There must never have been a time when the use of AI-enabled systems were more prevalent than today to optimize operational performances. In this regard, the ability to update AI capabilities while ensuring data systems security is one of our priorities.Therefore, the objectives of the challenge are to:
Experience in various ML tasks such as:
Implementation of a software platform and tools able to update models and perform machine learning without sharing data. The POC will be realized jointly by first deciding a particular task performed by ML (such as object detection, identification such as satellite images, predictive maintenance, natural language processing). A dataset will be identified to be used as a support for the POC (Thales data or public data). Then, a reference will be made with a scenario of total sharing of information between the parties, especially of data. It will be required to define one or more scenarios of updating the model with limited sharing. Finally, the results will be compared between the reference scenario (total sharing) and the scenario(s) with limited sharing.