The bigger implications of Apple’s machine learning technology

Author

Kerry Liu and Rubikloud

September 8, 2016

Today, all eyes are on Apple.

Long hailed as a leader in technology, we’ve seen many interesting developments come out of the Cupertino office, especially today with the news about the new iPhone 7.

Though there are plenty of new updates and products, there’s also the question of what goes on behind the scenes to make these products possible.

The answer can largely be summed up in two words: “machine learning.”

Machine learning has been around for quite some time, whether we realize it or not. In fact, the very idea that we don’t notice it means the technology is effective, processing and learning from incredibly large amounts of data in real time, right underneath our noses. However, the term has just recently become commercialized and recognized throughout the media, resulting in a more indepth conversation around artificial intelligence among both consumers and technology professionals.

Laying the foundation

Apple has laid some solid groundwork in this field. Take Steven Levi’s article on the iBrain that dives into the intricacies of Apple’s machine learning technology. Though Siri is largely the “face” (for lack of a better word) of Apple’s machine learning efforts, this technology certainly doesn’t stop with her. Machine learning is working throughout Apple devices in ways that consumers don’t think twice about. For example, swiping the screen to get a shortlist of apps you might want to open, or a map location popping up to point out the hotel you booked. This widely used and consumer-facing artificial intelligence sets the bar in the tech industry, and has contributed to brands and consumers having a high set of expectations for their digital experiences.

The competition is heating up

Though Siri is a very popular use of artificial intelligence, she hasn’t been met without competition. Virtual assistants like Cortana are right around the corner and competition is fierce among tech companies to see who will lead the way. This is a pressure that Apple recognizes and is causing them to constantly take steps to improve their machine learning division in order to remain a leader in the space, especially ahead of the upcoming launch of their new products and updates. The most recent demonstration of this is the acquisition of machine learning and artificial intelligence company, Turi. Additionally, Apple announced that they will be extending Siri’s functionality beyond the iPhone, using the deep learning behind her intelligent technology to integrate with Apple laptops, watches, and TVs.

The bigger picture

There are bigger implications for brands and retailers beyond Siri. These efforts to enhance and expand machine learning across the suite of Apple products is a sign to brands and retailers that there should be a sense of urgency toward personalized omnichannel experiences.

Consumers have come to expect highly-tailored content that learns from their behaviors and reacts in real-time. If anything falls short, they’re quick to take their business elsewhere. Apple has recognized the need for machine learning to meet consumer demand at such a large scale. By increasing the efficiency and accuracy of content with enhanced machine learning algorithms, Apple is providing users with a 1-to-1 customer experience, which will ultimately translate into brand loyalty and increased revenue for the company.

Consumers’ expectations for personalized experiences are only going to increase and Apple has made it clear that they plan on meeting these demands. This means that the competition is going to have to continuously work to build out their deep learning capabilities if they want to keep up. And that applies not just Apple’s competitors, but their partners too.

Brands and retailers who respond by integrating machine learning will be able to easily integrate with Apple products to offer consumers the shopping experience they’re looking for.

Those who don’t seriously risk being left behind.

This article was written by Kerry Liu and Rubikloud from VentureBeat and was legally licensed through the NewsCred publisher network.

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