RAG vs. Skill vs. MCP vs. RLM
12 hours ago
- #AI-techniques
- #LLM
- #context-window
- Comparison of techniques (RAG, SKILL, MCP, RLM) to enhance LLM reliability and overcome context window limitations.
- RAG (Retrieval-Augmented Generation): Dynamically injects relevant knowledge into prompts using vector databases, suitable for static knowledge bases.
- SKILL: Enables LLMs to dynamically load specific capabilities/tools as needed, reducing token usage and improving efficiency.
- MCP (Modular Control Protocol): Standardizes LLM interactions with external systems, ideal for complex, stateful integrations.
- RLM (Recursive Language Model): Bypasses context limits by recursively processing large datasets in a sandboxed environment.
- Each technique has pros and cons, tailored for different use cases like static data querying (RAG), dynamic tool usage (SKILL), or massive data processing (RLM).