The 6G Internet poses intense demands for intelligent and customized designs to cope with the surging network scale, dynamically time-varying environments, diverse user requirements, and complicated manual configuration. However, traditional rule-based solutions heavily rely on human efforts and expertise, while data-driven intelligent algorithms still lack interpretability and generalization. In this paper, we propose the AIGI (AI-Generated Internet), a novel intention-driven design paradigm for the 6G Internet, which allows operators to quickly generate a variety of customized network solutions and achieve expert-free problem optimization. Driven by the diffusion model-based learning approach, AIGI has great potential to learn the reward-maximizing trajectories, automatically satisfy multiple constraints, adapt to different objectives and scenarios, or even intelligently create novel designs and mechanisms unseen in existing network environments. Finally, we conduct a use case to demonstrate that AIGI can effectively guide the design of transmit power allocation in digital twin-based 6G networks.

翻译：6G互联网对智能化和定制化设计提出了强烈需求，以应对日益扩大的网络规模、动态时变环境、多样化的用户需求以及复杂的人工配置。然而，传统的基于规则的解决方案严重依赖人工干预和专业经验，而数据驱动的智能算法仍缺乏可解释性和泛化能力。本文提出AIGI（AI生成的互联网），一种面向6G互联网的新型意图驱动设计范式，使运营商能够快速生成多种定制化网络解决方案，并实现无专家问题优化。基于扩散模型学习方法的驱动，AIGI具有学习奖励最大化轨迹、自动满足多重约束、适应不同目标与场景的巨大潜力，甚至能智能创造现有网络环境中未见的新颖设计与机制。最后，我们通过一个用例证明，AIGI能够有效指导数字孪生6G网络中传输功率分配的设计。