News & Insights for the AI Journey|Friday, May 24, 2019
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Microsoft Transfers Vector Search To GitHub 

Since acquiring GitHub in June 2018, Microsoft has sought to make good on its pledge to retain the project collaboration platform’s “developer-first ethos.” This week it turned over to GitHub an AI search tool as an open-source project.

The vector search approach encapsulated in an algorithm called Space Partition Tree and Graph attempts to address the reality that growing data volumes have made keyword search “brittle.” The algorithm takes advantage of deep learning models to search collections of information known as “vectors” in milliseconds.

“As deep learning became more prevalent, we applied it to some of these problems keyword search wasn’t working for,” said Rangan Majumder, Microsoft’s group program manager for Bing search and AI.

The goal is to deliver relevant results faster using vectors, or numerical representations of a data point, word or image pixel. Hence, Majumder said his team built its vector search platform to executive search queries more efficiently.

While consumer applications based on vector searches are likely to emerge first, the contribution of the Space Partition Tree and Graph algorithm to GitHub also is intended to expand the framework to broader, enterprise applications, the company said this week in a blog post.

Read the full story here at sister web site Datanami.

 

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

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