The rapid advancement of generative artificial intelligence (AI) is reshaping communication paradigms through generative communications (GenCom), a novel paradigm for 6G networks. This article introduces the concept of GenCom, emphasizing its reliance on large AI models (LAMs) for semantic understanding, reasoning, and content generation, which are embedded into the communication process. Unlike traditional systems that strictly pursue accurate bit transmission, GenCom allows transmitters to convey only minimal yet sufficient information, while receivers leverage shared generative priors and knowledge bases to synthesize the intended output. Thus, communication is redefined as controlled generation rather than data reproduction.
We formalize the concept of GenCom, clarify its AI-native and generation-driven properties, and present its core mechanisms. A two-layer GenCom architecture supported by key enabling technologies is proposed, and an analysis of four representative application scenarios demonstrates that GenCom offers ultra-efficient transmission, semantic-level robustness, and new network functions. Finally, we outline future research directions, including foundational theory and real-time processing, highlighting a promising pathway toward 6G networks.
Blogger's Review: The introduction of generative communications marks a fundamental shift in communication technology, focusing not just on data transmission but on information generation and semantic delivery. This transition lays a new foundation for future 6G networks, warranting in-depth research and exploration.