  The last seventy years have witnessed the transition of communication from
Shannon's theoretical concept to current high-efficient practical systems.
Classical communication systems address the capability-deficiency issue mainly
by module-stacking and technique-densification with ever-increasing complexity.
In such a traditional viewpoint, classical source coding only uses explicit
probabilistic models to compress data, regardless of the meaning of transmitted
source messages. Also, channel coded transmission does not identify the source
content. In this sense, state-of-the-art communication systems work merely at
the technical level as summarized by Weaver. Unlike the traditional system
design philosophy, this article proposes a new route to boost the system
capabilities towards intelligence-endogenous and primitive-concise
communications. The communication paradigm upgrades to the semantic level,
which is radically different since all the key techniques imply the use of
meanings of transmitted data, thus deeply changing the design of the
communication system. This paradigm shifting unveils a promising direction due
to its ability to offer an identical quality of service with much lower data
transmission requirement. Different from other similar works, this article
constitutes a brief tutorial on the framework of semantic communications, its
gain analyzed from the information theory perspective, a method to calculate
the semantic compression bound, and an exemplary use case of semantic
communications.
