New Intelligence Report Editor: Hao Kun, Peach [New Intelligence Guide] ChatGPT’s capabilities have been unlocked, and its performance has been enhanced after adding plugin features. This is true for all large models. Tsinghua’s Wall Intelligence connects over 16,000 real APIs to large models, matching ChatGPT’s performance. Recently, open-source large language models (LLMs) have made rapid … Read more
Introduction 2024 is set to be a year of full bloom for AI Large Models, with major companies releasing their own large model application products, such as: • Tencent’s Yuanbao • Alibaba’s Tongyi Qianwen • Byte’s Doubao • Baidu’s Wenxiaoyan • The Dark Side of the Moon’s Kimi • And many more It’s a dazzling … Read more
CMAT: A 1.8B Agent Model Comparable to GPT-3.5 Release Date: April 2, 2024 Agent Artificial Intelligence Abstract Open large language models (LLMs) have greatly advanced natural language processing technology, excelling in numerous tasks. However, the effective use of LLMs still relies on human guidance to ensure smooth dialogue. Agent tuning techniques play an important role … Read more
Before getting into the main topic, let’s chat a bit. Many friends have seen me coding in my spare time. Sometimes I wonder why I do this; actually, my love for code has reached a somewhat obsessive level. There might be some bragging involved. Without further ado, everything has been revolving around agents lately, and … Read more
The open-source agent series focuses on introducing currently available open-source agent frameworks in the market, such as CrewAI, AutoGen, LangChain, phidata, Swarm, etc., discussing their advantages, disadvantages, features, effects, and usage. Interested friends can follow the public account “XiaozhiAGI” for continuous updates on cutting-edge AI technologies and products, such as RAG, Agent, Agentic workflow, AGI. … Read more
Are you still troubled by the mixed quality of AI services in the domestic market and poor performance? Then let’s take a look at DevCat AI (3in1). This is an integrated AI assistant that combines GPT-4, Claude3, and Gemini. It covers all models of the three AI tools. Including GPT-4o and Gemini flash Now, you … Read more
Overview As most LLMs are only trained periodically on a large amount of public data, they cannot access the latest information and/or private data. Retrieval-Augmented Generation (RAG) is a core paradigm for developing applications with LLMs, addressing this issue by connecting to external data sources. A basic RAG pipeline includes embedding user queries, retrieving relevant … Read more
Effectively parsing and understanding tables in unstructured documents remains a significant challenge when designing RAG solutions. This is especially difficult in cases where tables exist in image formats, such as scanned documents. These challenges include several aspects: The complexity of scanned or image documents, such as diverse structures, the presence of non-text elements, and the … Read more
Retrieval-Augmented Generation (RAG) is an emerging AI technology stack that enhances the capabilities of large language models (LLMs) by providing additional “up-to-date knowledge”. The basic RAG application includes four key technical components: Embedding Model: Used to convert external documents and user queries into embedding vectors Vector Database: Used to store embedding vectors and perform vector … Read more
Click on “Deephub Imba“, follow the public account, and don’t miss out on great articles! There have been many articles about Retrieval-Augmented Generation (RAG). If we could create a trainable retriever, or if the entire RAG could be customized like fine-tuning a large language model (LLM), we would definitely achieve better results. However, the current … Read more