AI Agents on AWS

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Understanding AI Agents on AWS

Standard LLMs are powerful but come with limitations, such as knowledge cutoff and the inability to access private or real-time data. This raises the question of how we can provide LLMs with information they don't have, or enable them to interact with the real world. Two key approaches address this without fine-tuning or retraining the entire model: Retrieval Augmented Generation (RAG), which gives the LLM relevant context from your data, and AI agents, which provide the LLM with the ability to reason and use tools to achieve goals.

You may have built a RAG system that can answer questions about you or your organization's data, only to find that your users want more. For example, they want the AI to actually ...