For beginners in machine learning, the most daunting aspects are the various formulas, concepts, and derivations. Faced with heavy textbooks and complex concepts, one often doesn’t know where to start. I used to struggle with the “Watermelon Book,” and when I saw examples like using watermelon vines to pick watermelons or judging the weather based … Read more
Written by丨Mony Researcher at Tencent Interactive Entertainment // Introduction As we know, we are deeply caught in the whirlpool of an artificial intelligence (AI) revolution. No matter which industry AI intervenes in, it brings revolutionary hopes and possibilities, while also triggering brand new challenges. For applications including large language models, generative AI, and semantic search, … Read more
Source: DeepHub IMBA This article is approximately 2600 words long and is recommended to be read in 8 minutes. For hallucinations in large language models (LLM), knowledge graphs have proven to be superior to vector databases. When using large language models (LLMs), hallucination is a common issue. LLMs generate fluent and coherent text but often … Read more
1 Algorithm Introduction Retrieval Augmented Generation (RAG) has become one of the hottest applications of large language models (LLM). After the recent boom in large models, everyone must have a certain understanding of their capabilities. However, when we apply large models to practical business scenarios, we find that generic foundational models generally cannot meet our … Read more
1. RAG (Retrieval Augmented Generation) RAG technology is a method that combines retrieval and generation. It typically relies on two core components: a large language model (such as GPT-3) and a retrieval system (such as a vector database). RAG first uses the retrieval system to extract relevant information from a vast amount of data, then … Read more
What is the hottest topic in the era of large models? In addition to ChatGPT, tools like LangChain and LlamaIndex, designed for building large model applications, have also been gaining significant attention. To help everyone get started easily, we launched the 【Decoding LangChain】 tutorial series, and now we present the 【Unveiling LlamaIndex】 series, which you … Read more
Pinecone + LangChain: Building an Efficient AI Retrieval System Recently, while experimenting with AI retrieval systems, I found that Pinecone and LangChain are a match made in heaven. Pinecone is a powerful vector database, and LangChain is a flexible framework. Combining the two allows you to easily build an efficient AI retrieval system. Today, I … Read more
To avoid losing contact, please also follow the backup account. Large language models are machine learning models capable of generating natural language text based on context. In recent years, with the development of deep learning and big data, the performance and capabilities of language models have significantly improved, leading to the emergence of many applications … Read more
Building an AI Memory System with LangChain and Pinecone from Scratch Recently, have you been overwhelmed by various AI applications? With the emergence of ChatGPT, Wenxin Yiyan, and more, it can be dazzling. However, did you know that these AI applications all share a common point – they utilize a magical framework called LangChain. Today, … Read more
Build Your Own AI Knowledge Base with LangChain and Pinecone Do you want to have your own AI assistant that can answer all your questions? With LangChain and Pinecone, you can easily achieve this! In this article, we will discuss how to use these two tools to build a personal AI knowledge base, making your … Read more