Home > AI Solutions > Gen AI > White Papers > Dell Scalable Architecture for Retrieval-Augmented Generation (RAG) with NVIDIA Microservices > Why RAG and LLM? Significance of Generative AI Chatbots
Integrating RAG with generative AI chatbots marks a paradigm shift in chatbot development and deployment. Traditional chatbots, constrained by the scope of their training data, often need help with responding to queries requiring specialized or current knowledge accurately. RAG addresses this limitation by empowering chatbots to retrieve and incorporate external data into their responses, improving their accuracy, reliability, and relevance.
The combination of RAG and LLMs presents a powerful solution that bridges the gap between retrieval-based and generative chatbots, creating a private, secure LLM that can parse and index your data within your data center. This synergy addresses security concerns associated with storing private, sensitive information in a cloud with an AI model by reversing the traditional model - it brings AI to your data instead of bringing your data to AI.