Real ChatGPT answer · index seedyK11DckMl24completeB2B software · AI and automation toolsinformational
How does vector search actually work under the hood and what steps can I take to improve the precision of retrieved embeddings in our company search tool?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How does vector search actually work under the hood and what steps can I take to improve the precision of retrieved embeddings in our company search tool?
1 real search · 1 real-search pass
vector search retrieval precision hybrid search reranking chunking evaluation official documentation embeddingsGoogle ↗
OBSERVEDReason
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (1)
Classes come from the query-classifier (a local Laya model). 1 of 1 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT1 real searches · gpt-6
vector search retrieval precision hybrid search reranking chunking evaluation official documentation embeddings Google ↗
- Hybrid Search Overview - Azure AI Search · learn.microsoft.com
- Hybrid search · docs.opensearch.org
- How to Perform Hybrid Search - MongoDB Vector Search · mongodb.com
- architecture-center/docs/ai-ml/guide/rag/rag-information-retrieval.md at main · MicrosoftDocs/architecture-center · github.com
- Query an AI Search index - Azure Databricks · learn.microsoft.com
- Vector search concepts · docs.opensearch.org
- Evaluate AI Search retrieval quality - Azure Databricks · learn.microsoft.com
- Vector Search Overview - Azure AI Search · learn.microsoft.com