  Modern communications are usually designed to pursue a higher bit-level
precision and fewer bits while transmitting a message. This article rethinks
these two major features and introduces the concept and advantage of semantics
that characterizes a new kind of semantics-aware communication framework,
incorporating both the semantic encoding and the semantic communication
problem. After analyzing the underlying defects of existing semantics-aware
techniques, we establish a confidence-based distillation mechanism for the
joint semantics-noise coding (JSNC) problem and a reinforcement learning
(RL)-powered semantic communication paradigm that endows a system the ability
to convey the semantics instead of pursuing the bit level accuracy. On top of
these technical contributions, this work provides a new insight to understand
how the semantics are processed and represented in a semantics-aware coding and
communication system, and verifies the significant benefits of doing so.
Targeted on the next generation's semantics-aware communication, some critical
concerns and open challenges such as the information overhead, semantic
security and implementation cost are also discussed and envisioned.
