  Recently, big artificial intelligence models (BAIMs) represented by chatGPT
have brought an incredible revolution. With the pre-trained BAIMs in certain
fields, numerous downstream tasks can be accomplished with only few-shot or
even zero-shot learning and exhibit state-of-the-art performances. As widely
envisioned, the big AI models are to rapidly penetrate into major intelligent
services and applications, and are able to run at low unit cost and high
flexibility. In 6G wireless networks, to fully enable intelligent
communication, sensing and computing, apart from providing other intelligent
wireless services and applications, it is of vital importance to design and
deploy certain wireless BAIMs (wBAIMs). However, there still lacks
investigation on architecture design and system evaluation for wBAIM. In this
paper, we provide a comprehensive discussion as well as some in-depth prospects
on the demand, design and deployment aspects of the wBAIM. We opine that wBAIM
will be a recipe of the 6G wireless networks to build high-efficient,
sustainable, versatile, and extensible wireless intelligence for numerous
promising visions. Then, we provide the core characteristics, principles, and
pilot studies to guide the design of wBAIMs, and discuss the key aspects of
developing wBAIMs through identifying the differences between the existing
BAIMs and the emerging wBAIMs. Finally, related research directions and
potential solutions are outlined.
