Cancel
About Andrey Vasnetsov
Andrey Vasnetsov is an author known for his contributions to the field of vector search, including articles on dedicated vector search services and binary quantization, as well as presentations on integrating SaaS platforms and the architecture of Qdrant's vector search engine.
Known information
| Andrey Vasnetsov is a prolific author in the realm of vector search technologies. He authored an article titled ‘Vector Search as a dedicated service,’ which discusses the necessity of having a dedicated service for vector search. Vasnetsov also contributed to the ‘Neural Search Tutorial,’ an article that provides a comprehensive guide on building a neural search service using BERT, Qdrant, and FastAPI. His expertise extends to the technical aspects of vector indexing, as evidenced in his discussion on binary quantization in the article ‘Binary Quantization - Andrey Vasnetsov | Vector Space Talks.’ Furthermore, Vasnetsov has shared valuable insights on the integration of SaaS platforms into workflows and the benefits of using Qdrant for database management in a talk titled ‘Qdrant x Dust: How Vector Search helps make work work better - Stan Polu | Vector Space Talks.’ His presentation provided an in-depth look into the intricacies of Qdrant’s open-source vector search engine and database, detailing its optimized architecture, data structure challenges, and innovative filtering techniques for efficient vector similarity searches. |
About Qdrant
Qdrant is a company that provides a vector database and similarity search engine, supporting AI applications with advanced search technologies and a variety of data types.
Report inaccurate information
