To effectively implement <span>RAG</span>, there are indeed many aspects that need refinement, and today we will learn about the Reject Module. Official Explanation In the RAG (Retrieval-Augmented Generation) model, the Reject Module is an important component designed to enhance the robustness of the generation model when facing irrelevant queries or information. Plain Explanation A simple … Read more
Introduction This sharing is titled “RAG 2.0 Engine Design Challenges and Implementation”. Main content includes the following parts: 1. Pain points and solutions of RAG 1.0 2. How to effectively Chunking 3. How to accurately recall 4. Advanced RAG and preprocessing 5. How RAG will develop in the future 6. Q&A Guest Speaker｜Zhang Yingfeng Founder … Read more
“ Hello everyone, this is Goodnote. The knowledge notes on large models RAG & Agent have been updated. The total word count is over 50,000. Due to space limitations, this article will only provide a summary. For detailed notes, please enter our public account and reply with ‘RAG’ and ‘Agent’ to obtain them. RAG Notes … Read more
Alibaba: AirRAG Enhances Complex QA Reasoning Capabilities! 🌟 Introduction 1️⃣ As the complexity of tasks increases, RAG faces new challenges, including the difficulty of retrieving sufficient knowledge in a single query and understanding the complex reasoning logic in questions. 2️⃣ This article proposes AirRAG, which activates intrinsic reasoning capabilities and expands the solution space by … Read more
ff ↑ Subscribe to us, get a wealth of free tutorial resources 1. What is RAG? – A Super Assistant That Can Retrieve and Generate Have you ever encountered this problem: when asking a large model, it can answer many questions, but sometimes it also “makes things up” or only provides information based on its … Read more
In the field of artificial intelligence, large language models (LLMs) have achieved significant accomplishments. However, due to their reliance on static training data, they often struggle to respond effectively to dynamic real-time queries. Retrieval-Augmented Generation (RAG) technology has emerged, bringing new hope to address this issue. Agentic RAG further breaks through the limitations of traditional … Read more
Reply ‘data’ to receive a collection of algorithm interview questions (large models, deep learning, machine learning). 1. What is Retrieval-Augmented Generation (RAG)? RAG is a hybrid approach that combines retrieval systems and generative language models. It consists of two steps: Retrieval Component: Searches for relevant information in large external corpora or datasets based on the … Read more
Click the “blue text” to follow us In today’s rapidly changing artificial intelligence (AI) technology landscape, major tech companies are launching innovative products aimed at providing smarter and more efficient solutions for enterprises and individual developers. Recently, Google Cloud announced the full launch of its Vertex AI RAG Engine (Retrieval-Augmented Generation Engine), which has garnered … Read more
Hello, I am the Fisherman. Today, I am sharing a 35-page overview of the latest Agentic RAG. The core problem this paper aims to address is the outdated, inaccurate outputs, and hallucinations that arise when today’s large language models (LLMs) rely on static training data to handle dynamic, real-time queries. It starts from the fundamental … Read more
I used Cursor to code, and my boss thought I was “cheating”! “Xiao Xiao, your coding speed is unbelievable! You finished a feature that we estimated would take two days in just an hour?” My boss stood behind me, staring at my screen with suspicion. “Hehe, boss, I have a genius helping me!” I turned … Read more