From Static to Smart: How RAG in Generative AI Makes Models More Adaptive
Artificial Intelligence has evolved rapidly, but generative models still struggle to stay current because they rely on pre-trained data, making their knowledge static after training. And the solution lies in Retrieval-Augmented Generation (RAG) in Generative AI addresses((i.e., solves or mitigates) this limitation by dynamically connecting large language models (LLMs) to external, authoritative data sources. This […]
