So you built a RAG. That's awesome!
LLMs often produce hallucinations, creating responses that seem factual but are false. Techniques like Retrieval-Augmented Generation (RAG) aim to mitigate this but fall short.
In this content piece, you'll read about:
✔Understanding RAG: How it integrates external data to improve LLM outputs.
✔Limitations of RAGs: Why RAGs might enhance coherence but don’t eliminate false information.
✔Effective Alternatives: How to provide real-time filtering, ensuring reliable and relevant responses.
