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Machine learning has quickly become a hot topic in information technology. And while it’s a big game changer now, it’s been on the technology and innovation scene for a few years now. Apple, for example, first brought Siri to light in 2011, but it was many years earlier that it first began experimenting with consumer-driven machine learning.

The iPhone and machine learning

Today, Siri is woven into our everyday experiences, and while we probably overlook the sophisticated technology, the AI ​​and machine learning aspects are truly remarkable—and truly pervasive in all aspects of our favorite virtual assistant. At its most basic level, Siri allows you to:

• Caller identity using emails, not just a contact list

• Swipe your screen to get a short list of apps you’re most likely to use

• Reminder of an appointment that you do not have on your calendar

• Maps showing the location of the hotel where you have a reservation before you ask

• Update from where you parked your car to where you parked your car

• Selected news

• Recognition of faces and places based on photographs

• When to switch from using a weak Wifi signal to a mobile network

• Using photos and video to create an unsolicited mini-movie

According to reports regarding Apple’s use of AI, the dynamic cache that allows the iPhone to learn takes up about 200 megabytes, depending on how much personal information is also stored. The system always deletes older data, so there is enough storage space.

In addition, search engines including Google use Google Now on your smartphone to process queries. For example, it knows you’re listening to a specific song when you ask, “Who’s the lead singer?”

The AI-fueled Apps Revolution

That’s just one application – AI is also fueling a renaissance in mobile applications as a whole. For example, mobile fitness apps with artificial intelligence will be able to continuously monitor your activities without your intervention. This instantly allows these apps to track your every step and continuously monitor your heart rate.

Another fast-growing app? Using artificial intelligence to enable your smartphone to verify your identity, making passwords and PINs obsolete. This could be done by facial recognition or several other unique identifiers.

In these use cases, the process is the same – machine learning algorithms are used on smaller screen devices. As technology expands, more and more memory and battery power are needed to perform processing. As a result, the data must be transferred to the server to run the algorithms. The system always deletes older data, so there is enough storage space.

The next step in innovation on the small screen

So how do you get there? Companies like WorkFusion are developing ways to run machine learning algorithms more efficiently using handheld and small-screen devices—like cameras, robots, smartphones, and smartwatches. For example, WorkFusion’s Cognitive Automation software facilitates machine learning that extends to images, documents, and PDFs. This on-demand webinar walks prospective users through four strategies for adopting AI techniques—consider this a primer if you’re interested in integrating machine learning in a user-friendly, organizationally seamless way.

And from there? The possibilities are endless for businesses large and small. Learn more about the tools necessary to connect your organization with the automation, artificial intelligence, and machine learning needed to take your processes to the next level.

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