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大模型技术的发展为融合生物人、数字人和机器人的平行人系统构建提供了崭新思路和智能基础。但是，在面临复杂系统的管控任务时，仍然存在着知识更新受限、专用能力不足以及信息隐私泄露等问题。为此，提出了检索增强生成驱动的平行人与平行智能框架——RAG-PHI，打造了开放式数据平台，为平行人系统接入实时知识、行业知识及私有知识；构建动态路由检索，进行上下文抓取和平行人能力重组；引入上下文提示学习增强思维与行为能力。进一步，面向平行人的组织管理、培训评估和运营生产模式，提出了基于RAG-PHI架构的平行人社区、平行人学校和平行人工厂架构，形成了检索增强生成和基础大模型协同驱动下的平行人生态，促进智业时代的生产力提升。

随着人工智能和虚拟现实等技术的发展，数字化技术正不断丰富和改变着人们的生活体验与生产方式，并成为管控复杂系统的有力工具。元宇宙与平行系统为数字化系统的建设提供了可行途径，在科学研究和产业应用中获得了广泛关注。综述了元宇宙与平行系统的发展现状，分析了两者的区别与联系，并对其未来发展进行了展望，预期为智能产业、智能经济及智能社会的发展提供一定的参考与借鉴。

随着新能源设备的大规模接入，大电网系统的脆弱性、开放性和不确定性显著上升，系统的管理与控制面临重大的挑战。构建基于平行系统与元宇宙思想的平行电网系统，形成虚实融合的智能大电网管理与控制理论方法，是解决上述问题的一种可行途径。介绍平行电网系统MetaGrid的基本体系架构，在此基础上分析平行电网系统的关键技术，并展望平行电网潜在的应用场景。基于300节点热稳案例，提供一个平行电网应用案例的原型。期望通过构建平行电网系统，对实际电网系统进行精准建模，借助大规模的计算实验和虚实闭环的平行执行，实现实际电网系统和人工电网系统的虚实互动，促进电力系统从依赖仿真的管控走向基于平行电网的智能管理与控制。

针对大数据时代广泛存在的数据孤岛问题，从整体入手，提出了联邦生态的基本框架，并探讨了其结构和运行机制。联邦生态以数据隐私可控为前提，以区块链技术为支撑，以联邦智能为驱动，借助联邦控制实现数据联邦化，通过联邦管理实现服务联邦化。为打破数据孤岛问题，联邦生态充分发挥了大数据和人工智能的潜力，进而为实现联邦智能提供了一种新的思路。

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Intelligent Science & Technology is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

大语言模型和视觉语言模型在各领域的应用中展示出巨大潜力，成为研究热点。然而，幻觉、知识迁移、与人类意图对齐等问题仍然影响着大模型的性能。首先，探讨了提示工程与对齐技术基本原理，提出基于提示优化、专家反馈机制及实时调整机制的引导概念，提升了大语言模型在跨领域应用中的性能；其次，深入分析提示工程的核心技术，如多步推理处理复杂任务的原理；然后，针对各领域的实际应用，讨论提示工程的发展现状；最后，总结提示工程面临的挑战并展望其未来发展方向。提示工程在理论与应用方面的发展，为提升大模型在实际应用中的性能提供了全面的解决方案。

旅游作为一种满足人们对不同生活体验和知识需求的活动，对经济、文化等领域都产生了深远影响。随着物联网、多模态大语言模型等技术的迅速发展，传统的旅游业难以满足人们智能化以及个性化的旅游需求。为此，以平行智能为理念，基于ACP方法与多模态大语言模型提出了虚实交互的个性化旅游服务系统，通过构建旅游大模型，并结合检索增强生成方法和多智能体协作系统，打造个性化旅游服务的新范式。此外，探讨了平行旅游的应用生态，从“行”“住”“食”“衣”4个方面对整个旅游生态进行拓展，分析了其他行业与个性化旅游服务的融合。平行旅游将为旅游行服务业的发展带来全新可能。