Machine learning has quickly become a hot button topic in information technology. And, although it's changing the game in a big way right now, it's actually been kicking around in the tech and innovation scene for several years. Apple, for example, first brought Siri into the light in 2011 but, years earlier, had first begun experimenting with consumer-driven machine learning.
The iPhone and Machine Learning
Today, Siri is woven into our day-to-day experiences and, though we likely overlook the sophisticated technology, the AI and machine learning aspects are truly remarkable -- and truly omnipresent in all aspects of our favorite virtual assistant. At its most basic level, Siri enables:
• Caller identity using emails and not just a contacts list
• Swiping the screen to obtain a short list of apps that you are most likely to use
• A reminder of an appointment not put on your calendar
• Maps showing the location of the hotel where you have a reservation before you ask
• Updates on where you parked your car last to where you parked your car
• Curated news stories
• Recognizing faces and locations based on photos
• When to switch from using a weak Wifi signal to a cell network
• Using photos and video to create an unprompted mini-movie
According to reports concerning Apple's use of AI, the dynamic cache that allows an iPhone to learn takes up about 200 megabytes depending on the amount of personal information that is also stored. The system is always deleting older data so there is enough storage space.
Moreover, search engines including Google uses Google Now on your smartphone to process queries. For example, it knows you are listening to a particular song when you ask, "Who is the lead singer?"
The Apps Revolution Spurred By AI
That's just one application -- AI is also spurring the reinvention of mobile apps as a whole. For example, mobile fitness apps with AI will be able to continuously track your activities without any input from you. This instantly enables these apps to track every step you take and monitor your heart rate continuously.
Another fast emerging application? Leveraging AI to enable your smartphone to authenticate your identity, making passwords and PIN codes obsolete. This could be performed by facial recognition or a variety of other unique identifiers.
In these use cases, the process is the same -- machine-learning algorithms are used on smaller-screen devices. As the technology expands, more and more memory as well as battery power is needed to perform the processing. As a result, data has to be transferred to a server to allow the operation of the algorithms. The system is always deleting older data so there is enough storage space.
The Next Step in Small Screen Innovation
So how to get there? Companies like WorkFusion are developing ways to run machine learning algorithms more efficiently, using handheld and small-screen devices -- think cameras, robots, smartphones and smart watches, among others. For example, WorkFusion's Cognitive Automation software facilitates machine learning extending across images, documents, and PDFs. This on-demand webinar walks prospective users through four strategies for adopting AI techniques -- consider this a go-to primer if you're interested in integrating machine learning in a user-friendly and organizationally seamless way.
And from there? The possibilities are endless for both big and small businesses. Find out more about the tools necessary to connect your organization to the automation, AI and machine learning needed to take your processes to the next level and beyond.
Article Source: https://EzineArticles.com/expert/Robert_K_Janis/2514709