Big AI Models for 6G Wireless Networks: Opportunities, Challenges, and Research Directions

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 zeroshot, learning, and exhibit state-of-the-art performances. As widely envisioned, the big AI models can rapidly penetrate into major intelligent services and applications, and are able to run at low unit cost with 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, investigation into architecture design and system evaluation for wBAIM is still lacking. In this article, 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 for 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.