As search needs evolve, Microsoft makes AI tools for better search available to researchers and deve

Only a few years ago, web search was simple. Users typed a few words and waded through pages of results.

Today, those same users may instead snap a picture on a phone and drop it into a search box or use an intelligent assistant to ask a question without physically touching a device at all. They may also type a question and expect an actual reply, not a list of pages with likely answers.

These tasks challenge traditional search engines, which are based around an inverted index system that relies on keyword matches to produce results.

“Keyword search algorithms just fail when people ask a question or take a picture and ask the search engine, ‘What is this?’” said Rangan Majumder, group program manager on Microsoft’s Bing search and AI team.

Of course, keeping up with users’ search preferences isn’t new — it’s been a struggle since web search’s inception. But now, it’s becoming easier to meet those evolving needs, thanks to advancements in artificial intelligence, including those pioneered by Bing’s search team and researchers at Microsoft’s Asia research lab.

“The AI is making the products we work with more natural,” said Majumder. “Before, people had to think, ‘I’m using a computer, so how do I type in my input in a way that won’t break the search?’”

Microsoft has made one of the most advanced AI tools it uses to better meet people’s evolving search needs available to anyone as an open source project on GitHub. On Wednesday, it also released user example techniques and an accompanying video for those tools via Microsoft’s AI lab.

The algorithm, called Space Partition Tree And Graph (SPTAG), allows users to take advantage of the intelligence from deep learning models to search through billions of pieces of information, called vectors, in milliseconds. That, in turn, means they can more quickly deliver more relevant results to users.