The new generation of wireless communication technologies is already in development. Sixth Generation (6G) mobile communications are designed to push the limits for more bandwidth, more connected devices with minimal power requirements, and better signal quality. Previous technologies used in Fifth Generation (5G) are inadequate to handle the new requirements alone. One of the proposed solutions is the use of Reconfigurable Intelligent Surfaces (RISs). These surfaces, when combined with Artificial Intelligence (AI), may be a very powerful means of achieving this. In this paper, we review studies that focus on the use of RISs controlled by AI in determining the concept of Smart Radio Environment (SRE) for use in 6G wireless networks. We examine applications that span from Supervised to Federated Learning (FL) as enabled by the rise in Edge Computing. As the new generation of mobile devices is expected to have enhanced capabilities to perform computing and AI locally, thus reducing the need to transfer the data to a central hub, more opportunities are created for the extensive use of FL. In this context, we focus on research in FL as used in RIS-aided SRE.