Microsoft Research is a globally distributed playground for people interested in solving fundamental science problems.
These projects often focus on machine learning and artificial intelligence, and since Microsoft is on a mission to infuse all of its products with more AI smarts, it’s no surprise that it’s also seeking ways to integrate Microsoft Research’s innovations into the rest of the company.
Across the board, the company is trying to find ways to become more innovative, especially around its work in AI, and it’s putting processes in place to do so. Microsoft is unusually open about this process, too, and actually made it somewhat of a focus this week at Ignite, a yearly conference that typically focuses more on technical IT management topics.
At Ignite, Microsoft will for the first time present these projects externally at a dedicated keynote. That feels similar to what Google used to do with its ATAP group at its I/O events and is obviously meant to showcase the cutting-edge innovation that happens inside of Microsoft (outside of making Excel smarter).
To manage its AI innovation efforts, Microsoft created the Microsoft AI group led by VP Mitra Azizirad, who’s tasked with establishing thought leadership in this space internally and externally, and helping the company itself innovate faster (Microsoft’s AI for Good projects also fall under this group’s purview). I sat down with Azizirad to get a better idea of what her team is doing and how she approaches getting companies to innovate around AI and bring research projects out of the lab.
“We began to put together a narrative for the company of what it really means to be in an AI-driven world and what we look at from a differentiated perspective,” Azizirad said. “What we’ve done in this area is something that has resonated and landed well. And now we’re including AI, but we’re expanding beyond it to other paradigm shifts like human-machine interaction, future of computing and digital responsibility, as more than just a set of principles and practices but an area of innovation in and of itself.”
Currently, Microsoft is doing a very good job at talking and thinking about horizon one opportunities, as well as horizon three projects that are still years out, she said. “Horizon two, we need to get better at, and that’s what we’re doing.”
It’s worth stressing that Microsoft AI, which launched about two years ago, marks the first time there’s a business, marketing and product management team associated with Microsoft Research, so the team does get a lot of insights into upcoming technologies. Just in the last couple of years, Microsoft has published more than 6,000 research papers on AI, some of which clearly have a future in the company’s products.
The group is also tasked with building tools and services for Microsoft’s customers to help them innovate on top of the company’s existing offerings. “We do think that the next breakthroughs are going to come from companies across every vertical, not just technology providers,” she said.
But setting up this group wasn’t always an easy sell. “People don’t understand what it means to increase consideration of something, versus actually selling it at that point,” said Azizirad. To sell this vision to the rest of the company, she said, you need to have a narrative that speaks around AI for the whole company. “And the other narratives need to dock into that so we have the primary end-to-end view for innovation.”
She also notes that the team is charged with creating new categories and hence business opportunities for Microsoft. That’s not totally new for Microsoft, of course, but it’s the first time the company has put a process in place for it.
“We really want to open the windows to what comes next,” she said. “A lot of people think, ‘well, gosh, there’s a lot of interesting projects going on there but they don’t actually turn into anything.’ Well, you know, Project Oxford was turned into Cognitive Services, where all of the language features and translation in PowerPoint came from. That was the same sort of work. The work around autonomous systems. We’re working with Gurdeep [Pall – the head of Micorosft’s Business AI unit] and Harry Shum’s organization [the Artificial Intelligence and Research Group] to bring that together.”
One of the areas the team is focusing on, for example, is natural interfaces, be that voice interactions or eye-tracking, but also fundamental work on opening up the black box that a lot of AI models still are today.
In practical terms, having a team that takes a broader look across disciplines and groups allows Microsoft to combine the various innovations across research teams. “The engineers get very focused on their own area. And so coming with the vision and the creativity and imagination of ‘wow, if we put this with this and this,’ which is what we do on our team, [that’s] more of the product management aspect of [what we do]. A lot of times, people don’t have a purview of what’s going on across the company. That’s differentiated for us.”
Indeed, applied innovation is very much what the team focuses on, said David Carmona, General Manager for AI at Microsoft. To do that, the team brings together software engineers and subject matter experts from both its internal groups and partners. One of the practical results is the work Microsoft is doing around autonomous systems and its AirSim simulation tool for training them, which is already paying off. At Microsoft Research, the team established a process that makes it easier for teams to have regular syncs across business units so the innovation can flow both across units and everybody is aware of what’s going on.
But this is indeed very much an effort that focuses on partners as well. Microsoft AI set up an AI Business School to help business leaders better understand what these AI technologies can (and can’t) do for their businesses — and understand how to do so in the right way.
“How do you put a strategy in place? How do you think about the cultural implications? How do you do it responsibly? We have a module on technology, but the technology module — while pretty — Responsible AI and Culture are the most popular, and we’ve already had half a million people go through that in less than a year,” said Azizirad. She did note, though, that for many companies, figuring out how to use AI responsibly is still on the back burner.
Going forward, Microsoft AI will likely bring more of the tools that the company is building internally to others. Internally, it’s already doing a lot of this, but the team isn’t quite ready to talk about most of this work externally yet. But at Ignite, the team is going to talk about more of the research the various teams are doing around AI — and in some cases, it’s even making the source code for these projects available.
One of these is Project Silica, which aims to store large amounts of data on a small piece of glass. But it’s also talking about how it looks at machine teaching as the next frontier for machine learning, for example, as well as a research project that looks at how cells process data in biology, and how to bring more intelligence to the clothes we wear by adding sensors that can track pollution, for example.
This is definitely a different Microsoft — one where changes like this come from the top.
For the longest time, Microsoft had a reputation for putting different groups in competition with each other. I don’t think that’s completely gone yet, but projects like this, that actually aim to enhance the communication between groups to share knowledge surely go a long way. It also opens up a faster path for a lot of the work in Microsoft Research to become productized faster.
