Editing Draft:Retrieval Techniques (section)

==Purpose and Benefits==
*   '''Addressing "Spiky Aspects" of Knowledge''': Retrieval is particularly effective for handling "spiky aspects" – discrete, factual, or rapidly changing information that might be difficult to encode directly into a model's weights through fine-tuning alone.
*   '''Complementary to Fine-tuning''': While fine-tuning is noted for capturing "illegible aspects" (subtle behaviors or stylistic nuances), retrieval excels at providing explicit, factual information, making the two approaches complementary.
*   '''Enhanced Performance and Accuracy''': By supplying relevant context, retrieval mechanisms ensure that crucial information is explicitly present in the prompt, leading to improved overall performance and more grounded generations. This helps models avoid "mode collapse" and reduces repetitive or irrelevant outputs.
*   '''Knowledge Expansion and "Second Brain" Functionality''': Retrieval allows ems to act as a "second brain" capable of accessing and incorporating vast amounts of external information, making them more knowledgeable and versatile.