--- ## Topics to cover * Evolution of search * Traditional approaches and drawbacks * Vectors search and how it harnesses ML models * Qdrant * Building HNSW index and vector search * Beyond similarity search: * Recommendations * Discovery * Sparse vectors
Replace search space image
Image showing vector search
--- ## How discovery uses that? ##### Remember Metric Learning?  ---
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## How multi-modal embeddings look like?  ---  ---  ---
## Sparse vectors * VS text search * BM25 & TF-IDF * Transformer's attention weights * SPLADE  ---
* Navigating search (read vector) space is powerful!
* Thank you!