Apple takes augmented reality and machine learning beyond “Big Data”

Augmented reality (AR) and machine learning (ML) technologies have been around for years, but until now their use has mostly been limited to processing massive volumes of cloud data for specialized industries and applications. For instance, AR applications have been used in military systems for years, and online retailers have always used some form of ML to better understand and influence buying decisions. Now, with the release of iOS 11 and the new iPad Pro, Apple is making these technologies accessible to a much broader group of developers and non-technical users alike.

Apple is known for democratizing very complex technologies by making them less expensive and easier to use. This is now the case with AR and ML in iOS 11 and iPad Pro. By providing the development tools needed to leverage these technologies, Apple is empowering a whole new generation of developers, consumers, enterprise users, and organizations to create their own customized applications that leverage AR and ML.

ARKit opens up a whole new market

AR has been heavily used in the gaming industry as well as training programs that involve complex machinery, such as military and airline equipment. For example, AR can teach users how to fix an engine by superimposing an image over a piece of live equipment to see how it functions in context. With the release of ARKit, Apple is now extending AR applications to hundreds of millions of potential users across any industry and skill level, and the creative possibilities are endless. For example, an architect could use an AR application on iPad Pro to superimpose a building concept over an image of the city to instantly visualize how the structure would impact the surrounding area.

Or imagine an IKEA app that allows the user to search for a household item, such as a cabinet. To see how the device would look in a particular room, a user with an iPad Pro accesses the image in the app, taps once to have the cabinet hover over the floor and then taps again to place. All the colors and dimensions are accurately represented as 3D models, giving the user a highly accurate representation of how the piece will really look and fit in the room. 1

Machine learning and the release of Core ML

While many ML algorithms have been around for a while, the ability to automatically apply complex mathematical calculations to big data and use the results to streamline business processes is fairly new. For example, Amazon or Netflix can automatically send users recommendations based on their purchase history. Or, based on a customer’s typical credit history, a financial services company can quickly detect possible credit card fraud, contact the customer, and shut down the account if necessary.

The release of Core ML in iOS 11 is a big step toward shifting artificial intelligence (AI) capabilities from the cloud to mobile devices. Core ML is a new framework API that’s designed to accelerate AI tasks on mobile devices including the iPhone, iPad Pro, and Apple Watch. Core ML won’t just process highly visible tasks like face recognition, it can also be used to customize the device interface based on the user’s behavior and optimize Siri’s responses based on the user’s inquiries. It’s important to note that Core ML is intended for on-device processing, so the data won’t be able to leave a user’s iOS device, which should help alleviate privacy concerns.

The initial release of ARKit and Core ML is designed to make it easy for developers to include these technologies in their apps. Because Apple has made ARKit and Core ML available to third-party app developers, we can expect to see a massive expansion in the ecosystem of AR- and ML-enabled apps. Although Apple isn’t alone in its efforts to expand AR and ML to new users and applications, Apple is exceptionally good at democratizing these technologies by making them cheaper and more accessible to a huge global base of non-technical users.

Want to learn more about what iOS 11 means to the enterprise? See our latest white paper here. You can also read our customer case studies to find out why thousands of MobileIron customers have already chosen iOS as their mobile platform.



Anne D'Angelo