Unlocking the Potential of Retrieval-Augmented Generation (RAG)
Acuvate
MARCH 2, 2025
In the rapidly advancing field of artificial intelligence, Retrieval-Augmented Generation (RAG) stands out as a transformative approach. By merging external knowledge with Large Language Models (LLMs), RAG overcomes the limitations of static training datasets, resulting in more dynamic, accurate, and context-aware outputs. Why RAG Matters Traditional LLMs are constrained by the data available at their training time, leading to challenges in addressing recent developments or rapidly changing topi
Let's personalize your content