Equipped with sensing, networking, and computing capabilities, Internet of Things (IoT) such as smartphones, wearables, smart speakers, and household robots have been seamlessly weaved into our daily lives. Recent advancements in Generative AI exemplified by GPT, LLaMA, DALL-E, and Stable Difussion hold immense promise to push IoT to the next level. In this article, we share our vision and views on the benefits that Generative AI brings to IoT, and discuss some of the most important applications of Generative AI in IoT-related domains. Fully harnessing Generative AI in IoT is a complex challenge. We identify some of the most critical challenges including high resource demands of the Generative AI models, prompt engineering, on-device inference, offloading, on-device fine-tuning, federated learning, security, as well as development tools and benchmarks, and discuss current gaps as well as promising opportunities on enabling Generative AI for IoT. We hope this article can inspire new research on IoT in the era of Generative AI.

翻译：具备感知、组网与计算能力的物联网设备（如智能手机、可穿戴设备、智能音箱及家用机器人）已深度融入日常生活。以GPT、LLaMA、DALL-E及Stable Diffusion为代表的生成式人工智能最新发展，展现出将物联网推向新高度的巨大潜力。本文阐述了生成式人工智能为物联网带来的优势，并探讨其在物联网相关领域中最具代表性的应用场景。在物联网中充分释放生成式人工智能的潜力面临复杂挑战。我们识别出若干关键挑战，包括生成式AI模型的高资源需求、提示工程、设备端推理、任务卸载、设备端微调、联邦学习、安全性、开发工具与基准测试等方面，并分析了当前技术差距与推动生成式AI赋能物联网的潜在机遇。期望本文能为生成式人工智能时代的物联网研究提供新思路。