AI Fundamentals

 

  • Machine Learning
  • Deep Learning
  • Neural Networks
  • Natural Language Processing (NLP)
  • Computer Vision
  • Reinforcement Learning

Using Open Source Frameworks to Deploy Private RAG AI Applications in Universities

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Using Open Source Frameworks to Deploy Private RAG AI Applications in Universities

Author: Liu Ran Affiliation: China People’s Police University, Information Technology and Network Management Department Editorial Note In the wave of digital transformation, the information construction of universities is in full swing, with AI applications represented by large language models becoming an important topic for the construction of smart campuses. The One-Stop Service Platform, as an … Read more

Case Report: Hemophagocytic Lymphohistiocytosis with Rag1 Gene Mutation

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Case Report: Hemophagocytic Lymphohistiocytosis with Rag1 Gene Mutation

Authors: Zhao Xiaoyu, Jiang Nan, Liu Chunyan, Fu Rong Author Affiliation: Department of Hematology, Tianjin Medical University General Hospital Corresponding Author: Fu Rong, [email protected] Funding: National Natural Science Foundation (81870101, 81970115) Citation Format: Zhao Xiaoyu, Jiang Nan, Liu Chunyan, et al. Case Report: Hemophagocytic Lymphohistiocytosis with Rag1 Gene Mutation [DB/OL]. China Clinical Case Achievement Database, … Read more

Amino Acids Regulate mTORC1 Activity Through Rag GTPase Dimer

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Amino Acids Regulate mTORC1 Activity Through Rag GTPase Dimer

Actually, I rarely read such purely mechanistic articles, but since mTORC1 is a classic signaling pathway, some newly discovered mechanisms may still be helpful for future explorations. The mTOR signaling pathway is recognized as a target of rapamycin, and my main focus is on adaptive immunity. In recent years, a group of scientists led by … Read more

Using GPT-4 to Generate Training Data for Fine-tuning GPT-3.5 RAG Pipeline

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Using GPT-4 to Generate Training Data for Fine-tuning GPT-3.5 RAG Pipeline

Source: DeepHub IMBA This article is about 3200 words long, and it is recommended to read for 6 minutes. This article explores the new integration of LlamaIndex for fine-tuning OpenAI's GPT-3.5 Turbo. OpenAI announced on August 22, 2023, that fine-tuning of GPT-3.5 Turbo is now possible. This means we can customize our own models. Subsequently, … Read more

Mita AI Search: The Ideal AI Model for Academic Research

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Mita AI Search: The Ideal AI Model for Academic Research

This is the 9th article by Teacher Wang Jue introducing AIGC. Please refer to the previous articles: #ai Teacher Wang Jue’s AIGC Educational Application Collection —————————————— Although large models are amazing, they can help us with general document work But Teacher Wang Jue has always believed: For professional research and education, large models are not … Read more

Comparing LangChain and LlamaIndex Through 4 Tasks

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Comparing LangChain and LlamaIndex Through 4 Tasks

Source: DeepHub IMBA This article is approximately 3300 words long and is recommended for a 5-minute read. In this article, I will use two frameworks to complete some basic tasks in parallel. When using large models locally, especially when building RAG applications, there are generally two mature frameworks available: LangChain: A general framework for developing … Read more

Building RAG AI Assistants with PhiData: A Comprehensive Guide

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Building RAG AI Assistants with PhiData: A Comprehensive Guide

Introduction In the field of artificial intelligence, building an intelligent assistant that can understand and respond to user needs is a challenging task. PhiData, as an open-source framework, provides developers with the possibility to create AI assistants with long-term memory, rich knowledge, and powerful tools. This article will introduce the core advantages of PhiData, application … Read more

Does Fine-Tuning Models in Specific Domains Make Sense? A Case Study of BioRAG

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Does Fine-Tuning Models in Specific Domains Make Sense? A Case Study of BioRAG

BioRAG: A RAG-LLM Framework for Biological Question Reasoning The question-answering systems in the life sciences face challenges such as rapid discovery, evolving insights, and complex interactions of knowledge entities, necessitating a comprehensive knowledge base and precise retrieval. To address this, we introduce BioRAG, a retrieval-augmented generation framework that combines large language models. First, we parse, … Read more

ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

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ACL 2024: Cambridge Team Open Sources Pre-trained Multi-modal Retriever

Follow our public account to discover the beauty of CV technology This article shares the ACL 2024 paper PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers, open-sourced by the Cambridge University team, empowering multi-modal large model RAG applications, and is the first pre-trained general multi-modal late-interaction knowledge retriever. Paper link: https://arxiv.org/abs/2402.08327 Project homepage: https://preflmr.github.io/ Introduction The … Read more

BIORAG: A Breakthrough Framework for Biological Question Reasoning

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BIORAG: A Breakthrough Framework for Biological Question Reasoning

Source: Biological Large Models This article is approximately 3000 words long and is suggested to be read in 5 minutes. This article introduces an innovative biological question reasoning system that combines Retrieval-Augmented Generation (RAG) and Large Language Models (LLM). In today’s rapidly advancing life sciences field, efficiently processing and answering complex biological questions has always … Read more