  Deep learning enabled semantic communications have shown great potential to
significantly improve transmission efficiency and alleviate spectrum scarcity,
by effectively exchanging the semantics behind the data. Recently, the
emergence of large models, boasting billions of parameters, has unveiled
remarkable human-like intelligence, offering a promising avenue for advancing
semantic communication by enhancing semantic understanding and contextual
understanding. This article systematically investigates the large
model-empowered semantic communication systems from potential applications to
system design. First, we propose a new semantic communication architecture that
seamlessly integrates large models into semantic communication through the
introduction of a memory module. Then, the typical applications are illustrated
to show the benefits of the new architecture. Besides, we discuss the key
designs in implementing the new semantic communication systems from module
design to system training. Finally, the potential research directions are
identified to boost the large model-empowered semantic communications.
