Zhou Tianhong pointed out that the big language model has achieved major breakthroughs and has four major impacts on the banking industry. It has powerful natural language and unstructured data understanding and generation capabilities, and has also made breakthroughs in general reasoning capabilities. In-depth analysis of the technical principles and technological breakthroughs of the big...

In 2025, AI technology will change, and technologies such as MCP, RAG, Function Calling, Agent and fine-tuning will reshape future applications. Among them, RAG, as the "external brain" of the large model, retrieves external knowledge through the vector database to enhance the professionalism of the answer. This article deeply analyzes RAG and large model fine-tuning technology, model...

In the AI ​​era, large model knowledge bases face database query problems, such as incorrect results and instability. Introducing knowledge graphs has become a new idea, which is like a bridge between natural language and databases. It can define entities and relationships, standardize terms, optimize query paths, and integrate across databases. Want to learn more about what knowledge graphs...

In-depth analysis of the actual comparison of tens of millions of vector databases, including Milvus, Qdrant, Chroma, Weaviate, etc. Revealing to you how to choose the right database in large model development. The article also covers key content such as knowledge graph construction tools and what knowledge graphs are, helping you improve RAG related projects. Click to read for details!

Dipu Technology has been focusing on enterprise-level big models for 7 years, deeply decoupling industry know-how and data assets. Explore the principles of big model technology, analyze the current status of big model technology, and how to make enterprise data and knowledge "live"? Here are the answers. Learn more and enter Dipu Technology's big model knowledge base!

Explore innovative applications based on Redis in Golang. This article details how to build a document vector indexing and retrieval system (RAG). In-depth analysis of the RAG technical framework, covering key aspects such as system architecture and project operation. The project has been open sourced to provide valuable reference for developers. Come and click to read and learn more about RAG...

Explore efficient interaction methods for large AI models. This article explains the RACEF prompt word framework in detail. It is a structured tool to improve AI interaction effects. It consists of five key parts, such as restatement and supplementation, and is applicable to a variety of complex tasks. Learn about its application scenarios, compatible models, and advantages and disadvantages....

Explore the truth behind AI Agent and analyze its current status in the field of large language models. Sun Xin, vice president of Gartner, discusses in depth that domestic AI Agent is at its peak but faces many constraints, and companies should explore it with caution. Detailed explanation of the current status and principles of large model technology to help you gain insight into industry...

In-depth analysis of building a responsible large language model solution, covering mitigation measures at the data, model, and security system levels. In particular, the application of RAG technology is introduced, and the principle of RAG technology is explained in detail. It reveals how to reduce potential hazards and improve model security. Click to read for more details!

In-depth analysis of the differences between n8n and Dify in the fields of workflow automation and AI applications! Two open source star tools, n8n focuses on general workflow automation, and Dify focuses on AI-driven development. Compare their core functions, applicable scenarios, etc. in detail. Learn about the application of open source big models in them and interpret what open source big...