Measuring Embedding Drift: Why Hybrid Search Saves Stale Models.
Embedding drift, a phenomenon where AI models become outdated due to evolving language, can be mitigated by using hybrid search methods. This approach combines traditional keyword search with vector search, helping to maintain model relevance. By integrating these techniques, organizations can ensure their AI systems remain effective even as new terminology emerges. AI
IMPACT Hybrid search offers a practical method to maintain the performance of AI models over time by addressing vocabulary evolution.