Monday, May 20 • 10:50am - 11:10am
Deep Learning Vector Search Service

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Over the last couple of years, search has evolved beyond simple keyword-based information retrieval to more complex scenarios, such as natural language queries, Question-and-Answer, and multimedia search. Deep learning models are used to encode user intent and context into vector representations, which are then searched against billions of other vectors to find the most relevant results.

Deep Learning Vector Search Service (DLVS) is a low latency, large scale, and highly efficient vector search system at Microsoft, primarily used within the Bing search engine. This talk will discuss the key innovations in approximate nearest neighbor (ANN) algorithm and distributed vector index serving platform necessary to achieve this scale and performance.


Mingqin Li

Mingqin Li is the software engineering manager at Microsoft, who leads Bing's deep learning platform. Low latency, large scale, and highly efficient deep learning vector search service are developed for various scenarios like web search, similar image search, question-and-answering... Read More →

Jeffrey Zhu

Jeffrey Zhu is a program manager at Microsoft who drives the development of Bing's deep learning platform. This platform powers some of Bing's most innovative features, such as machine reading comprehension and visual search. It serves millions of deep learning model inferences per... Read More →

Monday May 20, 2019 10:50am - 11:10am
Stevens Creek Room

Attendees (10)