Hugging Face, a popular AI model hub, has released a new tutorial on using their transformers in conjunction with the distributed computing framework Ray. The tutorial, called Retrieval Augmented Generation (RAG), aims to improve natural language processing tasks such as question answering and text summarization by leveraging the strengths of both transformer models and retrieval-based methods. According to Hugging Face, RAG can help increase model performance on these tasks without requiring significant increases in computational resources. --- Why it matters: This matters because it provides a practical example of how to combine different AI techniques to improve performance on specific tasks, which is an important challenge for researchers and engineers working with natural language processing models. Source: https://huggingface.co/blog/ray-rag