  The traditional role of the network layer is the transfer of packet replicas
from source to destination through intermediate network nodes. We present a
generative network layer that uses Generative AI (GenAI) at intermediate or
edge network nodes and analyze its impact on the required data rates in the
network. We conduct a case study where the GenAI-aided nodes generate images
from prompts that consist of substantially compressed latent representations.
The results from network flow analyses under image quality constraints show
that the generative network layer can achieve an improvement of more than 100%
in terms of the required data rate.
