rag
-
The Efficiency of RAG Over Fine-Tuning LLMs: A Comprehensive Exploration
In the evolving landscape of artificial intelligence, Large Language Models (LLMs) have become pivotal tools. These models, such as GPT-3, GPT-4, and LLaMA 3, possess remarkable capabilities, revolutionizing various fields from natural language processing to automated content generation. However, as we delve deeper into optimizing these models, the debate between fine-tuning and using methods like Continue reading
-
Building an AI-Driven Document Query Assistant: A Step-by-Step Python Tutorial
Introduction This tutorial is designed to explain a Python script that utilizes various packages and techniques to create a sophisticated document-based question answering system. This system leverages the power of AI models to interpret and respond to user queries based on a repository of documents. It’s an excellent example of how to integrate multiple AI Continue reading
-
Building an AI-Driven Document Query Assistant: Using Non-OpenAI’s Embed Model
Yesterday, I published a blog post detailing the process of creating an Building an AI-Driven Document Query Assistant: A Step-by-Step Python Tutorial. However, upon further reflection, I realized that utilizing this assistant with a sizable dataset could prove costly due to its reliance on OpenAI’s embed model. To address this, I’ve reconfigured the code to Continue reading
-
Building an AI-Driven Document Query Assistant: New Update Supports GPT-4o and Incremental Re-Indexing
Please refer the references below to get up to speed on this project: This is a continuation update for the “Building an AI-Driven Document Query Assistant” series. In the last update, I implemented a non-OpenAI embed model, specifically the nomic-embed-text:latest using Ollama. In this update, I have added an incremental re-indexing feature and enabled users Continue reading
-
Unveiling the Brilliance of RAG AI: The Next Leap in Information Retrieval
In the rapidly evolving landscape of artificial intelligence, a groundbreaking technology emerges, casting a vibrant glow on the horizon of knowledge extraction and utilization. Known as Retrieval-Augmented Generation (RAG), this innovative AI model marries the depth of understanding with the precision of information retrieval, creating a hybrid system that is transforming how we interact with Continue reading
EssayBoard 