New research shows semantic caching can cut LLM inference costs by up to 73%—even when cache hits are misleading. The AdaptiveSemanticCache uses a QueryClassifier and similarity thresholds to decide when to reuse embeddings from a vector_store, dramatically reducing token usage. Curious how this works and how you can apply it to your own models? Read the full breakdown. #SemanticCaching #LLM #VectorStore #EmbeddingModel
🔗 https://aidailypost.com/news/semantic-caching-can-slash-llm-costs-by-73-despite-misleading-cache
