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Since ChatGPT became popular and "out of the circle", there has been a wave of AI large-scale models at home and abroad. More and more companies are starting to lay out the field of AI large-scale models, and many of them have launched their own AI large-scale model products, trying to take the lead in this wave of AI. Among the many AI large models, there are both general large models and vertical large models.
After the birth of AI large-scale model products, the landing and commercial application of AI large-scale models have become the focus of attention of all parties. At the same time, companies that release AI large-scale model products have also accelerated the speed of AI large-scale model landing and application exploration. Among them, the field of intelligent customer service is regarded by the outside world as one of the best positions for the implementation of AI large-scale models.
AI big model change intelligent customer service?
When it comes to intelligent customer service, I believe that most people will not feel unfamiliar. As user habits gradually shift to online, people's demand for customer service is increasing day by day. With the increasing demand for customer service, intelligent customer service has also been applied to assist manual customer service and bring better and more efficient services to users and consumers. Nowadays, the intelligent customer service industry has achieved rapid development and is becoming more and more popular. So, why does intelligent customer service become one of the best places for AI large-scale models to land?
First of all, the AI large model has excellent performance in content generation and semantic understanding, and has a high degree of fit with the intelligent customer service industry. Looking at many AI large-scale model products, it is found that the vast majority of large-scale model products have the capabilities of text generation, language understanding, knowledge question and answer, logical reasoning, etc. Due to the combination of deep learning and natural language processing technology, the language understanding ability and content generation ability of AI large model are particularly outstanding.
Intelligent customer service uses artificial intelligence technology to identify customer needs through speech recognition, natural language processing and other technologies, and gives targeted answers according to customer needs to answer customer doubts and enhance customer service efficiency. The language understanding ability and content generation ability of the AI large model are exactly what intelligent customer service needs. It can be seen that the AI large model has a high degree of fit with the field of intelligent customer service, and it is easier to implement landing applications.
Secondly, the AI large model can improve the intelligence of intelligent customer service to a certain extent. Although the emergence of intelligent customer service has alleviated the work pressure of traditional manual customer service to a certain extent, improved the work efficiency of customer service, and actually helped people solve some problems, it is undeniable that due to the limited intelligence of intelligent customer service , There are also endless complaints on the Internet about the fact that smart customer service is "not smart" and that smart customer service "doesn't understand human speech".
With the advent of the digital age, more and more data are produced, and the large AI model uses massive training data. Through the study of massive text data, the language understanding ability of the large AI model has also been continuously improved. The model has the ability to process more complex information. And with the intelligent customer service supported by AI large model, it can understand the context more accurately and identify user intentions, so as to provide customers with more reliable customer service.
China Mobile "Journey"
The popularity of AI large-scale models continues to remain high, and more and more participants have joined the competition of AI large-scale models, and operators are no exception. Specifically, China Unicom released the "Honghu" large-scale graphic model 1.0; China Telecom released the large language model TeleChat; ·Customer service model. The reason why China Mobile is the first to launch a large model for customer service is related to multiple factors.
On the one hand, China Mobile has accumulated many years in the field of customer service, and its service experience and profound business knowledge have laid a foundation for it to launch large-scale model products for customer service scenarios. For a long time, China Mobile, as the three major operators, has a deep connection with users. When users use mobile communication services, wireless Internet access and wired broadband services, they will inevitably encounter various problems that cannot be solved by individuals. At this time, users need to seek help from the operator's customer service. Over the years, China Mobile has accumulated massive data resources, rich customer service experience and professional business knowledge, and has a deep understanding of the customer service industry. These data and experiences have become important resources and resources for China Mobile to launch a customer service model. refer to.
It is understood that the nine-day customer service model can not only analyze questions and provide answers based on natural language descriptions provided by users; it can also collaborate with human customer service to analyze the semantics and context of historical communication content, summarize and summarize the key points and key information of the conversation, Provide suggestions for replies to human agents.
On the other hand, the customer service model launched by China Mobile can serve its own business and improve quality and efficiency . As mentioned above, China Mobile has a deep connection with users, and the data and experience it has accumulated in the field of customer service over the years have become important nutrients for China Mobile to train its customer service model. Similarly, the customer service model launched by China Mobile can also be applied to its own business to empower its own business, improve customer service efficiency and quality, and optimize user experience.
For example, in the face of complex questions raised by users, the nine-day customer service model can form a collaboration with human customer service. By analyzing the semantics and context of historical communication content, it can summarize and summarize the key information, provide reply suggestions for human customer service, and reduce responses. Time, so as to achieve the double improvement of manual customer service efficiency and user satisfaction.
Rong Lianyun "Let's Go"
Not long ago, Ronglian Cloud officially released the "Chitu Large Model", a vertical industry multi-level large language model for enterprise applications. It is understood that the Chitu large model focuses on communication, analysis, knowledge, and execution of the "four major capabilities" to escort intelligent customer service and marketing scenarios.
First, Ronglian Cloud began to explore AIGC very early, which provided important support for its launch of AI large-scale model products. It is understood that the Ronglian Cloud AI team has started research and development of AIGC key technologies a long time ago, and has made breakthroughs in dialogue reply generation, automatic question generation, and SQL statement generation. The core technology is listed in authoritative competitions and evaluation lists Achieved multiple first and Top rankings. The accumulation of these technologies has become an important driver for Ronglian Cloud to launch large language model products.
The second is that Ronglian Cloud has been deeply involved in the field of intelligent customer service, and has a deep industry understanding of intelligent customer service. It can launch AI large-scale model products with stronger intelligent customer service capabilities. For a long time, Ronglian Cloud has been deeply involved in the field of intelligent customer service, and has launched a variety of products such as intelligent customer service robots. Thanks to years of deep cultivation, Ronglian Cloud has a deeper and more thorough industry understanding and cognition of the intelligent customer service industry. Ronglian Cloud can rely on a large number of vertical industry resources accumulated over the years to train AI large-scale model products, and at the same time combine its deep understanding of the field of intelligent customer service to create the current large-scale model products.
For example, in the current field of intelligent customer service, intelligent customer service can basically realize accurate recognition and reply to common sentence structures, but when faced with complex sentence questions, intelligent customer service will appear to be unclear and not answer the question. The Chitu Big Model has the four core capabilities of "communication, analysis, knowledge, and execution". High-dimensional analysis and reasoning.
The third is that Ronglianyun launched a large-scale industry model, which makes it easier to realize commercialization. Although AI large models have broad development prospects, they are also very "burning money". Therefore, the commercialization of AI large models has also attracted attention. The industry model launched by Ronglianyun not only combines its understanding of the needs of the industry, but also magnifies its own original advantages, making it easier to realize commercialization. It is understood that based on the "Chitu Big Model", enterprises can build their own intelligent customer service and digital marketing, and complete the evolution from "cost reduction and efficiency increase" to "value creation".
challenges follow
Judging from the current situation, the AI large model and intelligent customer service do have a high degree of compatibility, and it is logical for intelligent customer service to become one of the important landing scenarios for the AI large model. However, it must be said that although the application of AI large models in the field of intelligent customer service has high value, it also faces challenges.
First, the quality of the content generated by the AI large model is not stable, and it cannot meet the needs of users for the time being. Different from other industries, smart customer service often needs to give accurate and reliable answers. One of the important reasons why smart customer service has been complained by users before is that smart customer service can't understand the user's meaning and answer the wrong question.
However, affected by the quantity and quality of training data, the content quality of the results given by the AI large model is not stable, and errors may even occur. Once the AI large model generates wrong answers, it will not only fail to achieve the original effect of using the AI large model to reduce costs and increase efficiency of intelligent customer service, but will even have a negative effect, reducing the customer service experience of customers.
Second, the customer service industry has a wide coverage and fast information iteration, which puts higher requirements on the AI model. The application of intelligent But at the same time, more training data means higher training costs.
All in all, the application of AI large models has been put on the agenda, and more and more companies are beginning to explore the application scenarios of AI large models and start to try. Smart customer service has become an important scene for the implementation of AI large models due to its inherent value and high degree of fit with AI large models. Although the implementation of AI large models in the field of intelligent customer service still faces many challenges, it is believed that these problems will be overcome one day. At that time, users may enjoy a truly intelligent and personalized intelligent customer service experience.