The 2024 World Artificial Intelligence Conference (WAIC), held from July 4 to 7 at the Shanghai World Expo Center, attracted numerous AI companies showcasing their latest technologies and applications. Among these, applications based on Large Language Models (LLM) and Generative AI (GenAI) were particularly highlighted. This article focuses on the Enterprise Brain (WPS AI) exhibited by Kingsoft Office at the conference and the underlying Retrieval-Augmented Generation (RAG) model, analyzing its significance, value, and growth potential in enterprise applications.
WPS AI: Functions and Value of the Enterprise Brain
Kingsoft Office had already launched its AI document products a few years ago. At this WAIC, the WPS AI, targeting enterprise users, aims to enhance work efficiency through the Enterprise Brain. The core of the Enterprise Brain is to integrate all documents related to products, business, and operations within an enterprise, utilizing the capabilities of large models to facilitate employee knowledge Q&A. This functionality significantly simplifies the information retrieval process, thereby improving work efficiency.
Traditional document retrieval often requires employees to search for relevant materials in the company’s cloud storage and then extract the needed information from numerous documents. The Enterprise Brain allows employees to directly get answers through text interactions, saving considerable time and effort. This solution not only boosts work efficiency but also enhances the employee work experience.
RAG Model: Enhancing the Accuracy of Generated Content
The technical model behind WPS AI is similar to the RAG (Retrieval-Augmented Generation) model. The RAG model combines retrieval and generation techniques, generating answers or content by referencing information from external knowledge bases, thus offering strong interpretability and customization capabilities. The working principle of the RAG model is divided into the retrieval layer and the generation layer:
- Retrieval Layer: After the user inputs information, the retrieval layer neural network generates a retrieval request and submits it to the database, which outputs retrieval results based on the request.
- Generation Layer: The retrieval results from the retrieval layer, combined with the user’s input information, are fed into the large language model (LLM) to generate the final result.
This model effectively addresses the issue of model hallucination, where the model provides inaccurate or nonsensical answers. WPS AI ensures content credibility by displaying the original document sources in the model’s responses. If the model references a document, the content is likely credible; otherwise, the accuracy needs further verification. Additionally, employees can click on the referenced documents for more detailed information, enhancing the transparency and trustworthiness of the answers.
Industry Applications and Growth Potential
The application of the WPS AI enterprise edition in the financial and insurance sectors showcases its vast potential. Insurance products are diverse, and their terms frequently change, necessitating timely information for both internal staff and external clients. Traditionally, maintaining a Q&A knowledge base manually is inefficient, but AI digital employees based on large models can significantly reduce maintenance costs and improve efficiency. Currently, the application in the insurance field is still in the co-creation stage, but its prospects are promising.
Furthermore, WPS AI also offers basic capabilities such as content expansion, content formatting, and content extraction, which are highly practical for enterprise users.
The WPS AI showcased at the 2024 WAIC demonstrated the immense potential of the Enterprise Brain in enhancing work efficiency and information retrieval within enterprises. By leveraging the RAG model, WPS AI not only solves the problem of model hallucination but also enhances the credibility and transparency of the content. As technology continues to evolve, the application scenarios of AI based on large models in enterprises will become increasingly widespread, with considerable value and growth potential.
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Enterprise Brain applications, RAG model benefits, WPS AI capabilities, AI in insurance sector, enhancing work efficiency with AI, large language models in enterprise, generative AI applications, AI-powered knowledge retrieval, WAIC 2024 highlights, Kingsoft Office AI solutionsRelated topic:
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