Evgeniya Sukhodolskaya
Developer Advocate at Qdrant with 8 years of IT experience across software engineering, machine learning, and developer advocacy.
Holds a Technical University of Munich master's degree in Data Analytics and Engineering.
Passionate about NLP and Information Retrieval.
Believes in conference-, complaints- and memes-driven development:)
Qdrant
Sessions
How does searching for new information often look? Loops: query, review results for relevance, rewrite the query, repeat… Until success, or until the user churns / the token budget burns.
This talk introduces a new instrument for search pipeline builders: propagating query-results relevance right inside the search algorithm of a search engine.
Why do we even need traditional search when AI can do everything? Or is it foolish to ignore simple, proven techniques for delivering great results? What's the best way to combine old and new? Join our panel of experts for a fun and provocative debate!