“ 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
This is the sixth article in the large model programming series, and also my notes from the free course on some cloud large model engineer ACA certification[1]. This course is really good, highly recommended! 👍🏻 If you’re interested in the course, please click the link at the bottom to view the original article. Here are … Read more
TrustRAG Project Address🌟: **https://github.com/gomate-community/TrustRAG** Configurable Modular RAG Framework Introduction to Chunking In the RAG (Retrieval-Augmented Generation) task, chunking is a critical step, especially when dealing with complex PDF documents.PDF documents may contain images, strange layouts, etc., which increases the difficulty of chunking. Impact of Chunk Granularity Sentence/Word Granularity: Focuses on local, key information queries but … 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 today’s rapidly advancing field of artificial intelligence, Retrieval-Augmented Generation (RAG) technology has become a hot topic for research and application due to its unique advantages. RAG technology combines the powerful generation capabilities of Large Language Models (LLMs) with efficient information retrieval systems, providing users with a new interactive experience. However, as the technology is … 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
LLM (Large Language Model, a powerful new platform) is a powerful new platform, but they are not always trained on data relevant to our tasks or the latest data. RAG (Retrieval Augmented Generation, a method that connects LLMs with external data sources (such as private data or the latest data). It allows LLMs to use … 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