Microsoft Promotes Cortana As Productivity Assistant Across Rival Platforms
With Amazon's Echo and Alexa dominating consumers' interest in connected intelligence, Microsoft is making a more subtle pitch to developers and consumers.
While Amazon, Google, and Apple have been attracting most of the attention for their respective connected intelligence devices and Alexa, Okay Google, and Siri voice-activated assistants, Microsoft has released a series of new features for its Cortana platform designed to appeal to developers first, early adopters second.
Given that these are still “early days” for connected intelligence in consumer electronics, Microsoft’s appeal to developers could position it for a range of partnerships that will become more important these tools become more central to home appliances, cars, as well as personal and professional devices.
“A few years ago, it was hard to think of a commonly used technology tool that used AI,” said Harry Shum, EVP, Microsoft AI and Research, speaking at the Build developer conference this week. “In a few years, it will be hard to imagine any technology that doesn’t tap into the power of AI.”
Competing on “what’s smarter” is a tough one at the moment — the differences and capabilities of artificial intelligence for consumer products are all fairly similar. Instead, Microsoft is appealing to developers’ and consumers’ resentment towards “walled gardens.”
At Microsoft’s Build conference, it began by highlighting that Cortana skills can run across the Redmond company’s Windows 10 and Office 365 suite, as well as Google Android, Apple iOS. And if that gets Microsoft some attention for its new Cortana-powered Harman Kardon Invoke speaker or MSFT XBox or Skype communication platform, all the better.
Aside from that, Microsoft is also adding new Cortana connections for its other products such as Bing search platform and Azure AI and Internet of Things programs.
“We now offer 29 Cognitive Services, giving developers a wealth of options for incorporating off-the-shelf and custom AI capabilities with just a few lines of code,” Shum said. “We also showed how developers can custom train this set of services without needing to design their own deep learning models.”