Exploring the future of AI, is RAG really dead? Actually not! RAG technology is not simply expanding the context window, but its principle is to inject external knowledge into the model in real time. It can make up for the limitations of pre-training data and solve the fatal weaknesses of the model such as the inability to access private data. Want to learn more about RAG technology? Click to...

Explore the innovative application of big models in the power industry, such as intelligent generation and verification of dispatching operation tickets and intelligent monitoring of illegal operations at production sites. Based on the big model knowledge base, integrate general and vertical models, build a knowledge graph, and improve work efficiency and safety. Smart hardware development and...

In-depth analysis of the RAG technical framework, comparing the core differences between LangChain and LlamaIndex in one article! From functional features to applicable scenarios, a comprehensive analysis of the two frameworks. Whether you want to flexibly build complex AI applications or focus on efficient data retrieval, there is always one that suits you. Click to read for details!

In-depth analysis of 25 RAG architectures to help you accurately select the right one for your AI project! In the AI ​​era, RAG is the key to extracting accurate answers. From the classic application of standard RAG to the optimization and correction of corrective RAG, different architectures have their own advantages. Covering a variety of real-world scenarios, we will show you the unique...

In-depth analysis of CAG and RAG to explore the status of large model technology. The article explains in detail how RAG works, such as obtaining external information on demand during inference to ensure that the latest relevant data is available. It also compares its key differences with CAG. Want to understand the principles of large model technology? Click to read and find out!

In-depth exploration of new possibilities of AI assistants, taking Manus as an example, showing its powerful functions in a virtual machine environment. Compared with common chatbots, Manus can not only "think" but also "do things", just like a smart intern. Especially in the field of smart hardware and smart hardware industry, Manus can complete complex tasks autonomously. Want to know more?...

In-depth analysis of RAG technology, summarizing and introducing 15 block segmentation strategies. Covering a variety of block segmentation methods such as fixed size, sentence-based, paragraph-based, and semantic-based, and analyzing their advantages and disadvantages in detail. Whether you are a technology novice or an experienced developer, you can get valuable information from it. Click to...

Explore the innovative achievements of the ByteBrain team at FSE25, using large language models to solve the oncall upgrade problem. In-depth analysis of the technical principles and architecture of the large model, revealing how it copes with the diversity and dynamic changes of oncall problems. Learn about the unique application of large language models in this field, click to read!

In-depth exploration of the field of AI big models, analyzing the current situation when AI protocols encounter poor engineering practices. Focusing on the MCP protocol, exploring its application and problems in big models. Understand the current status of big model technology, analyze the principles of big model technology, and reveal the layout and competition of major manufacturers. Come...

Explore the secrets of collaboration between application process documents and Cursor AI, and reveal the key role of RAG. Explain in detail how to improve collaboration efficiency and save development time through tools such as flowcharts and timing diagrams. Share model fine-tuning techniques, such as model fine-tuning methods and other practical content. Want to know more? Click to read!