Deloitte predicts 300M smartphones to feature machine learning capabilities in 2017

January 27, 2017 - 

Deloitte has published its “Technology, Media & Telecommunications (TMT) Predictions” report, which forecasts that over 300 million smartphones (more than 20 percent of units sold in 2017) will feature machine learning capabilities in the next 12 months.

The 16th edition of the report explores how mobile devices will be able to perform machine learning tasks even without connectivity, which will significantly impact the way humans communicate with technology across industry verticals, markets and societies.

The report emphasizes that machine learning on-the-go will not be restricted to smartphones, and that over time, these capabilities are likely to be featured in tens of millions of drones, tablets, cars, virtual or augmented reality devices, medical tools, Internet of Things (IoT) devices and new technologies.

“Machine learning is fascinating as it will revolutionize how we conduct simple tasks like translating content, but it also has major security and health consequences that can improve societies around the world,” said Paul Sallomi, vice chairman and global TMT industry leader of Deloitte LLP and U.S. technology sector leader. “For example, mobile machine learning is a strong entry point to improve responses to disaster relief, help save lives with autonomous vehicles, and even turn the tide against the growing wave of cyberattacks.”

Stuart Johnston, Deloitte leader of TMT practice, told Reseller News that he predicts that machine learning is a “megatrend”, driven by the high ownership of smartphones. He added that the technology’s application and influence will improve all facets of people’s lives in 2017, particularly in mobile.

“Machine learning is paving the way for a unique era in functionality, personalisation, and connectivity with other devices through our smartphones,” said Johnston. “It is enabling us to have a personalised computer in the form of a smartphone in our hands, with individualised services provided with or without connectivity.”

Machine learning programs are currently used in smartphones, including predictive text, suggestions for which application you want to load next, and biometrics such as voice and facial recognition, Johnston said.

In addition to machine learning, Deloitte predicts that biometric security will reach the billions in 2017.

According to Deloitte, the active user base of fingerprint reader-equipped devices will likely hit the 1 billion mark for the first time in early 2017.

In addition, Deloitte analysts estimate that each active sensor is used an average of 30 times a day, resulting in over 10 trillion aggregate presses globally over the year.

The extremely fast pace of access and adoption of biometric technology poses the challenge of determining which additional applications could use fingerprint readers and what other biometric inputs should be considered to provide rapid and secure authentication, Deloitte analysts said.

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About Justin Lee

Justin Lee has been a contributor with Biometric Update since 2014. Previously, he was a staff writer for web hosting magazine and website, theWHIR. For more than a decade, Justin has written for various publications on issues relating to technology, arts and culture, and entertainment. Follow him on Twitter @BiometricJustin.