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基于代理AI的混合专家与大型语言模型的联合计算与网络Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models
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以下内容为 AI 自动翻译，英文原文附后供参考。
摘要
近期AI的进展促成了一种新框架的开发，旨在优化第六代（6G）移动网络。该框架将混合专家（MoE）架构与大型语言模型（LLMs）相结合，实现了对专业优化专家的动态选择与协调。通过利用代理AI，该系统能够自适应地响应高层意图，从而在各种网络目标上实现近乎最佳的性能。这一创新方法标志着AI与电信交叉领域的重要进展，可能会改变网络的管理与优化方式。
Recent advancements in AI have led to the development of a novel framework aimed at optimizing sixth-generation (6G) mobile networks. This framework integrates mixture of experts (MoE) architectures with large language models (LLMs), enabling a dynamic selection and orchestration of specialized optimization experts. By leveraging agentic AI, the system can adaptively respond to high-level intents, thereby achieving near-optimal performance across various network objectives. This innovative approach marks a significant step forward in the intersection of AI and telecommunications, potentially transforming how networks are managed and optimized.
要点
将MoE架构与LLMs结合可以提升6G网络的性能。
The integration of MoE architectures with LLMs can enhance the performance of 6G networks.
代理AI使得网络优化专家能够根据用户意图进行动态协调。
Agentic AI enables dynamic orchestration of network optimization experts based on user intents.
该框架可能导致更高效和响应迅速的移动网络。
This framework could lead to more efficient and responsive mobile networks.
为何重要
该框架的发展标志着移动网络能力的重大飞跃，可能导致更快、更可靠的连接，能够实时适应用户需求。
The development of this framework signifies a major leap in the capabilities of mobile networks, potentially leading to faster, more reliable connectivity that can adapt to user needs in real-time.
产品经理
对于产品经理而言，这一创新为开发利用自适应网络能力的产品开辟了新途径，提升用户体验和满意度。
For product managers, this innovation opens new avenues for developing products that leverage adaptive network capabilities, enhancing user experiences and satisfaction.
开发者
开发者和工程师应探索在项目中整合代理AI和MoE架构的潜力，因为这可能导致电信领域更高效的算法和系统。
Developers and engineers should explore the potential of integrating agentic AI and MoE architectures in their projects, as this could lead to more efficient algorithms and systems in telecommunications.
学生与求职者
学生和求职者应考虑AI在电信中的影响，因为对这些新兴技术的专业知识在就业市场上将变得越来越有价值。
Students and job-seekers should consider the implications of AI in telecommunications, as expertise in these emerging technologies will be increasingly valuable in the job market.
覆盖来源
来源标题与摘录保留原文，以便核对与追溯。
arXiv cs.LG
Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language ModelsThe paper presents a framework for optimizing sixth-generation (6G) mobile networks by integrating mixture of experts (MoE) architectures with large language models (LLMs). This agentic AI-based approach allows for dynamic selection and orchestration of specialized optimization experts based on high-level intents, achieving near-optimal performance in various network objectives.