Microsoft is in a race with Google and Facebook to establish the strongest hold over people's digital lives. The changes at Microsoft Research resemble how its younger Silicon Valley rivals have operated for years. "Microsoft totally separated its research arm from the rest of the company and almost made it optional to contribute to the rest of the company," said Ahmad Abdulkader, an engineer on the applied machine learning team at Facebook who previously worked at Microsoft and Google. "Google took the exact opposite approach."

Google researchers work very closely with product groups, and almost everything they produce is visible to the rest of the company, said Jeff Dean, a senior fellow at Google. "We don't have this really isolated group that is doing stuff without any regard to what might be useful in products," he said. "We have this very porous connection between research and products."

Researchers and developers on the search engine or Gmail teams share many of the same tools, including the company's open-source AI framework TensorFlow, Dean said. That kind of close collaboration has helped produce impressive features, including Smart Reply, which suggests e-mail responses based on the content of a message. The feature, released in November 2015, was based on about a year of AI research at Google. Once the company decided to deploy the tech in Google's Inbox app, it took around four months to produce a prototype, said Jason Freidenfelds, a Google spokesman.

A similarly ambitious effort at Facebook, aimed at developing a conversational AI assistant called M, was born from research that began in 2014. The company published a paper on its work in October 2014, and by summer 2015 the tech was ready to be tested in Facebook Messenger. Alex Lebrun, who leads development of Facebook M, meets weekly with the company's top AI researchers to explore which lab developments are ready for the world. Facebook employees can track research-in-progress using a tool named FBLearner Flow. It lets them access, copy, and adapt the source code, and then deploy their own versions of the software, said Abdulkader, the Facebook machine learning engineer. "This is how experiments are exposed and shared."

Facebook Chief Technology Officer Mike Schroepfer said the cooperation between its research labs and those working on the social network is an effective recruiting tool. "The promise I made to all the artificial intelligence folks that joined us is we're going to be the best place to get your work to a billion people as fast as possible," Schroepfer said during an event last year at the company's headquarters in Menlo Park, Calif.

One potential drawback of this approach is it could encourage scientists to ignore projects that don't have obvious financial potential. Each company is trying to strike a balance to avoid this breed of short-term thinking. For instance, Facebook assigns some staff to focus on long-term research, and Google's DeepMind group in London conducts pure AI research without immediate commercial considerations.