On December 17, Glonghui reported that Kaichun shares (301001.SZ) stated during an investor relations event that AI language models, generative models, and sentiment models are developing rapidly in the e-commerce industry. The company has widely adopted AI technology in key business areas such as content operation, image design, data collection and processing, and customer service contact, achieving automation and intelligence in business processes. By introducing RPA (Robotic Process Automation) and AI technology, the company has empowered customer service reception and conversion in the pre-sale, in-sale, and after-sale stages, significantly improving service quality and efficiency. In terms of operation management, the company has refined through intelligence and digitalization, enhancing work efficiency through visual design and algorithm optimization. Generative models can accelerate the output in design roles, allowing brands to quickly see demos in an efficient sea of images, reducing redundant time in repeated modifications. These improvements not only enhance operational efficiency but also enhance the user experience. In terms of internal training, the combination of multiple models can provide personalized learning paths, automatically adjusting training content based on employees' skill levels and learning progress. For example, by combining natural language processing (NLP) and machine learning models, employee learning data can be analyzed to provide customized learning materials and feedback, thus improving training effectiveness. In internal collaboration, the combination of multiple models can optimize workflows and enhance team collaboration efficiency. For example, combining chatbots and knowledge graphs can create intelligent assistants to help employees quickly find information, coordinate tasks, and solve problems, reducing repetitive work and improving work efficiency. Through these combined applications of multiple models, the company can not only improve operational efficiency but also reduce operational costs, achieving optimal resource allocation. This technology-driven operational optimization is one of the key strategies for the company to maintain competitiveness in the digital age. In the future, the company will continue to focus on the latest application scenarios of AI technology and actively explore the integration of AI technology with e-commerce scenarios to enhance the company's overall core competitiveness. At the same time, the company is committed to continuously improving its R&D and technology development capabilities by building intelligent and digital business models, utilizing Cloud Computing, Big Data analysis, and AI, to enhance operational efficiency and decision-making quality. The company will combine digital methodologies with its main business to address the pain points faced by brands in a targeted manner, achieving dual improvements in service quantity and quality. Through these efforts, the company aims to provide customers with more personalized and efficient services while optimizing internal management processes to achieve sustainable development.