Martin Oywamartinoywa.hashnode.dev·Apr 21, 2024Retrieval Augmented Generation (RAG) - A Simple Theoretical Introduction.Introduction Over the last year, the popularity of Large Language Models (LLMs) has soared significantly, with use cases in almost all major industries popping up, mostly through chat interfaces or chatbots. With this popularity, the question of how ...Discuss·1 like·87 readsRetrieval-Augmented Generation
Alvin Leealvinslee.hashnode.dev·Apr 8, 2024How to Implement RAG: A Simple WalkthroughHaving the correct data to support your use case is essential to a successful implementation of LLMs in any business. While most out-of-the-box LLMs are great at general tasks, they can struggle with specific business problems. They didn’t train on ...Discusslarge language models
Farhan Naqvifarhanbytemaster.hashnode.dev·Apr 2, 2024How context window of LLMS cause hindrance in RAG appsA comprehensive overview of the challenges posed by restricted context windows in Retrieval-Augmented Generation (RAG) apps:. Token Limit and Context window in RAG: Large Language Models (LLMs): RAG models often rely on pre-trained LLMs for the gene...DiscussAI
Farhan Naqvifarhanbytemaster.hashnode.dev·Apr 1, 2024What do you mean by fine tuning a LLM ?Large Language Models are sophisticated models trained on vast amounts of text data and are capable of understanding and generating human-like text. Fine-tuning a LLM allows you to use the pre-trained knowledge of the model to perform specific tasks ...DiscussAI
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 30, 2024Issues with RAG applicationsRetrieval-Augmented Generation (RAG) is a powerful technique, but it does come with some challenges: Finding Relevant Documents: The retrieval process is crucial, as RAG relies on identifying relevant documents to inform the generation process. If t...DiscussAI
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 29, 2024Internal working of a RAG ApplicationLarge Language Models (LLMs) are powerful tools, but their capabilities are limited by the data they're trained on. They lack access to private user data and the ever-growing stream of newly published information. This challenge along with the limita...Discussworking of rag
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 28, 2024Components of a RAG ApplicationRAG (Retrieval-Augmented Generation) includes three main components: Embedding Model: This model takes textual information (queries, documents, etc.) and transforms them into numerical representations called "embeddings." These embeddings capture th...Discussgenerative ai
Farhan Naqvifarhanbytemaster.hashnode.dev·Mar 26, 2024#RAGMatters : Why Retrieval-Augmented Generation is Revolutionizing AIWe've all likely used ChatGPT at some point in our lives. These large language models (LLMs) are impressive, allowing us to ask questions like "Explain the concept of a black hole" , “What is Love?”, “How to get Abs in 10 minutes?”. If you are using...Discuss#RAGMatters
Sanjay Nandakumarsanjay7907.hashnode.dev·Mar 20, 2024Retrieval-Augmented Generation (RAG): Revolutionizing NLP with External KnowledgeIntroduction The realm of Natural Language Processing (NLP) is witnessing a paradigm shift with the emergence of Retrieval-Augmented Generation (RAG). This innovative technique goes beyond the limitations of traditional models by seamlessly integrati...Discussnlp
Yash SaxenaforDevelop with Yashdevelopwithyash.hashnode.dev·Mar 5, 2024AI & Java : Integrating GPT with SpringBoot using SpringAI, Retrieval Augmented Generation(RAG) and PG Vector DatabaseIn today's dynamic software development landscape, staying ahead means integrating cutting-edge technologies seamlessly into our projects. Spring Boot, with its rapid application development capabilities, is a popular choice for building enterprise-l...Discuss·104 readsSpringAi
