The article explores the relationship between Large Language Models (LLMs) and Retrieval Augmented Generation (RAG), depicting them as a complementary pair in AI communication. LLMs are adept at generating human-like text but sometimes produce incorrect information due to their lack of memory and reliance on learned patterns. RAG, on the other hand, serves as a reliable partner, providing real-time facts and context to enhance the accuracy of the conversation. The synergy of LLMs and RAG leads to a more trustworthy and engaging interaction experience, balancing creativity with factual integrity.
RAG enhances LLMs by providing accurate, up-to-date information, ensuring that this AI duo—one creative, the other factual—delivers reliable and engaging interactions.
While LLMs generate text from patterns, RAG retrieves information to keep conversations grounded and accurate, creating a symbiotic relationship between creativity and factuality.
Collection
[
|
...
]