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AI for Good-Innovate for Impact



               Use case – 51: A New Mode and Practice of Human-Robot

               Interaction Operation and Maintenance Based on Network Large
               Language Model (AI Chat Operations, AIChatOps)                                                       51-China Telecom









               Country:   China

               Organization:   China Telecom Jiangsu Branch

               Contact Person: Wenhan Rong
                                           +86 15301582482
                                          rongwh@ chinatelecom .cn


               51�1� Use case summary table

                Domain                Telecommunications
                The problem to be     Traditional network maintenance lacks real-time scheduling based
                addressed             on intent, relying on manual operations or limited automation.

                Key aspects of the    Using Large Language Model (LLM) for intent recognition, mobile
                solution              data query, and execution. Implementing ChatOps for human-robot
                                      interaction in network maintenance.

                Technology keywords   Large Language Model (LLM), AI Chat Operations, ChatOps,
                                      Network Maintenance Automation

                Data availability     Data is privately available.

                Metadata (type of     Textual data, Numerical data, Categorical data, Image data, and
                data)                 Video data

                Model Training and    Fine-tuning LLM for task scheduling and parameter completion.
                fine-tuning           Implementing multi-agent systems for execution efficiency.

                Testbeds or pilot     Not publicly available
                deployments 



               51�2� Use case description


               51�2�1� Description

               Existing problem: Traditional network maintenance mainly relies on manual operation and
               equipment inspection or network management systems to carry out specific and inherent
               automated operations, which cannot realize real-time scheduling based on intent.                          

               Solution: (1) Develop the ability to quickly query and execute data on mobile devices. (2)
               Based on the intention recognition ability of the Large Language Model、LLM、, retrieve the
               most similar automation capabilities and extract the parameters based on the natural language
               instructions input by the user. (3) Based on the network LLM intelligent agent technology,



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