Abstract
With the rapid development of artificial intelligence, machine learning, and deep learning, intelligent customer service systems have become a crucial component of automated customer service and intelligent management. This study conducts an in-depth investigation into the current status of intelligent customer service systems, highlighting the challenges faced by intelligent systems. Of particular concern is the significant challenge in generating meaningful, long-lasting, and information-rich customer service responses, despite the tremendous progress of artificial intelligence in many fields. To address this issue, based on a literature review, this study selects leading natural language processing technology (NVIDIA NeMo) and data mining tools (RISELab Ray). By combining these cutting-edge technologies, we propose innovative improvements and solutions aimed at enhancing the quality and efficiency of intelligent customer service systems.
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