Definition
In RAG and AI Agent architectures, time complexity quantifies how the computational resource requirements scale relative to increases in vector database size (N), document length, or the number of iterative reasoning steps in an agentic loop. It primarily dictates the feasibility of real-time retrieval (e.g., O(log N) vs O(N)) and the efficiency of processing long-context prompts.
Focuses on theoretical scaling growth (Big O) of search and inference, rather than specific wall-clock latency measured in milliseconds.
"Finding a specific book in a pile on the floor (Linear Search) versus finding it using a library's Dewey Decimal System (Indexed Search)."
- HNSW (Hierarchical Navigable Small World)(Component)
- Approximate Nearest Neighbor (ANN)(Optimization Technique)
- Inference Latency(Practical Metric)
- Vector Indexing(Prerequisite)
Conceptual Overview
In RAG and AI Agent architectures, time complexity quantifies how the computational resource requirements scale relative to increases in vector database size (N), document length, or the number of iterative reasoning steps in an agentic loop. It primarily dictates the feasibility of real-time retrieval (e.g., O(log N) vs O(N)) and the efficiency of processing long-context prompts.
Disambiguation
Focuses on theoretical scaling growth (Big O) of search and inference, rather than specific wall-clock latency measured in milliseconds.
Visual Analog
Finding a specific book in a pile on the floor (Linear Search) versus finding it using a library's Dewey Decimal System (Indexed Search).