In recent years, artificial intelligence (AI) and machine learning (ML) are reshaping society's production methods and productivity, and also changing the paradigm of scientific research. Among them, the AI language model represented by ChatGPT has made great progress. Such large language models (LLMs) serve people in the form of AI-generated content (AIGC) and are widely used in consulting, healthcare, and education. However, it is difficult to guarantee the authenticity and reliability of AIGC learning data. In addition, there are also hidden dangers of privacy disclosure in distributed AI training. Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition. The above information security issues in the coming era of AI powered by LLMs will be infinitely amplified and affect everyone's life. Therefore, we consider empowering LLMs using blockchain technology with superior security features to propose a vision for trusted AI. This paper mainly introduces the motivation and technical route of blockchain for LLM (BC4LLM), including reliable learning corpus, secure training process, and identifiable generated content. Meanwhile, this paper also reviews the potential applications and future challenges, especially in the frontier communication networks field, including network resource allocation, dynamic spectrum sharing, and semantic communication. Based on the above work combined and the prospect of blockchain and LLMs, it is expected to help the early realization of trusted AI and provide guidance for the academic community.

翻译：近年来，人工智能（AI）与机器学习（ML）正重塑社会生产方式和生产力，同时也改变着科学研究的范式。其中，以ChatGPT为代表的AI语言模型取得了巨大进展。此类大语言模型（LLM）以AI生成内容（AIGC）的形式服务人类，广泛应用于咨询、医疗和教育等领域。然而，AIGC学习数据的真实性和可靠性难以保障。此外，分布式AI训练中还存在隐私泄露隐患。同时，LLM生成的内容难以识别与溯源，且难以实现跨平台互认。上述信息安全隐患在即将到来的以LLM驱动的AI时代将被无限放大，并影响每个人的生活。因此，我们考虑利用具有卓越安全特性的区块链技术赋能LLM，提出可靠AI的愿景。本文主要介绍区块链赋能大语言模型（BC4LLM）的动机与技术路线，包括可靠的学习语料、安全的训练过程以及可识别的内容生成。同时，本文还回顾了潜在应用与未来挑战，特别是在前沿通信网络领域，包括网络资源分配、动态频谱共享和语义通信。基于上述工作结合以及区块链与LLM的展望，有望助力可靠AI的早日实现，并为学术界提供指导。