Analysis
This article dives into the exciting world of Retrieval-Augmented Generation (RAG) and AI Agents, two key technologies transforming how we use Large Language Models (LLMs). By integrating external databases and enabling agents to interact with systems, RAG and AI Agents are pushing the boundaries of what LLMs can achieve in business applications.
Key Takeaways
- •RAG enables LLMs to access and utilize external knowledge, overcoming limitations of pre-trained models.
- •AI Agents expand LLMs' capabilities by allowing them to interact with and operate external systems.
- •Careful data preparation, including cleaning and formatting, is crucial for effective RAG implementation.
Reference / Citation
View Original"RAG (Retrieval-Augmented Generation) is a system that allows a Large Language Model (LLM) connected via an API to generate responses after searching and referencing an external database (such as internal company information)."