治理幻觉的方式有很多,包括在训练时提供更高质量的数据,对模型进行Finetune补充领域内知识,在RLHF给予Reward Model关于数据真实性更高的倾向性,通过Prompt引导大模型避免对缺乏信息的问题进行生成,以及本文所提到Retrieval Augment Generation,基于向量数据库的召回式生成。合理利用幻觉,可以充分发挥大模型
In this blog, we’ll embark on a journey to create a RAG (Retrieval-Augmented Generation) Question and Answer system. Don’t worry if the terms sound complex; we’re here to break it down into simple steps. Langchain, a powerful language tool, teams up with OpenAI’s advanced models to...
RAG(Retrieval-Augmented Generation,检索增强生成)是一种结合信息检索与大语言模型(LLM)生成能力的 AI 技术。其核心思想是:在 LLM 生成回答前,先从外部知识库检索相关内容,将检索结果与用户问题一同输入 LLM,提升生成结果的准确性、时效性和可溯源性。 典型应用场景: 企业知识库问答、智能客服 文档/合同/论文智能摘...
Learn to build a fully-functional chatbot application (with UI) with RAG (Retrieval-Augmented Generation) capabilities using Spring AI and Spring Web.About Us HowToDoInJava provides tutorials and how-to guides on Java and related technologies. It also shares the best practices, algorithms & solu...
人工智能的法庭书记员是一个称为检索增强生成(retrieval-augmentedgeneration,简称RAG)的过程。 “RAG” 的由来 帕特里克·刘易斯 (Patrick Lewis) 是2020 年创造该术语的论文的主要作者,他为这个不讨人喜欢的缩写词道歉,该缩写词现在描述了数百篇论文和数十种商业服务中日益壮大的方法系列,他认为这些方法代表了生成式...
One of the most powerful applications enabled by LLMs is sophisticated question-answering (Q&A) chatbots. These are applications that can answer questions about specific source information. These applications use a technique known as Retrieval Augmented Generation, orRAG. ...
Think of RAG (Retrieval-Augmented Generation) as giving an AI chatbot access to your own knowledge base. Instead of relying only on what it learned during training, the AI can look up specific information from your knowledge base to give you more answers to queries from your own data. ...
What are the benefits of retrieval-augmented generation? There are three key benefits of RAG: 1. Relevant information RAG provides current and reliable sources to LLMs, ensuring users receive the latest information. 2. Improved user confidence ...
Retrieval-augmented generation (RAG) is a method that enables users to converse with data repositories. It’s a tool that can revolutionise how you access and utilise data, as we showed in our tutorial. With RAG, you can improve data retrieval, enhance knowledge sharing, and enrich the resul...
We will take a look at how to set up a RAG – Retrieval Augmented Generation – demo with the Anthropic Claude 3 Sonet model, using google’s CoLab platform. CoLab offers free instances with T4 GPUs sometimes, but we’ll only need a simple CPU instance, since we access the model only ...