RAG (Retrieval-Augmented Generation) is a promising future for LLMs, particularly in domains with dynamic or private knowledge, as it reduces hallucinations by integrating real-time, relevant data. However, the expense and complexity of large context windows suggest that efficient, selective data retrieval will remain crucial. Alternatives like advanced memory management and fine-tuning overlays are also promising solutions.