AI is still evolving and reshaping the world of technology with new possibilities of what machines are capable of. Another modern development in the AI, and more specifically in the NLP, is called Retrieval-Augmented Generation (RAG). This new approach takes the best from generative models and retrieval-based techniques, thus producing more accurate and contextually relevant…
Retrieval and generation in NLP have set the stage for more complex models such as the Retrieval-Augmented Generation (RAG). RAG integrates retrieval models and generative models to provide better and contextually appropriate answers. In this guide, you will learn how to apply RAG for NLP applications, including data preprocessing, choosing a model, incorporating retrieval models,…
Over the years, artificial intelligence has introduced various developments and among them, we have the Retrieval-Augmented Generation (RAG). RAG blends the performance of retrieval-based models with generative models, thus enhancing the information retrieval and response generation. This blog discusses future developments of RAG, new ideas, and the field’s potential uses in different sectors including healthcare…
