Recently, big artificial intelligence (AI) models represented by chatGPT have brought an incredible revolution. With the pre-trained big AI model (BAIM) 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 present the core characteristics and principles 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.

翻译：近期，以ChatGPT为代表的通用人工智能大模型带来了革命性突破。借助特定领域预训练的大模型，仅需少量样本甚至零样本学习即可完成众多下游任务，并展现出最先进的性能。正如广泛预期，大模型将快速渗透至主要智能服务与应用领域，能够以低单元成本和高灵活性运行。在6G无线网络中，为实现智能通信、感知与计算的全面赋能，除提供其他智能无线服务与应用外，设计部署特定无线大模型具有关键意义。然而，当前对无线大模型的架构设计与系统评估尚缺乏系统性研究。本文围绕无线大模型的需求、设计与部署层面展开全面讨论与深度前瞻。我们认为无线大模型将成为6G无线网络构建高效、可持续、多功能且可扩展无线智能的关键方案，以支撑众多前景广阔的应用愿景。继而，我们提出指导无线大模型设计的核心特征与原则，通过剖析现有通用大模型与新兴无线大模型间的差异，探讨开发无线大模型的关键维度。最后，本文概述了相关研究方向与潜在解决方案。