  Prior to the era of artificial intelligence and big data, wireless
communications primarily followed a conventional research route involving
problem analysis, model building and calibration, algorithm design and tuning,
and holistic and empirical verification. However, this methodology often
encountered limitations when dealing with large-scale and complex problems and
managing dynamic and massive data, resulting in inefficiencies and limited
performance of traditional communication systems and methods. As such, wireless
communications have embraced the revolutionary impact of artificial
intelligence and machine learning, giving birth to more adaptive, efficient,
and intelligent systems and algorithms. This technological shift opens a road
to intelligent information transmission and processing. This overview article
discusses the typical roles of machine learning in intelligent wireless
communications, as well as its features, challenges, and practical
considerations.
