“The big new thing in smartphones lately is one of those buzz phrases you’ll have heard tossed around: machine learning. Like augmented and virtual reality, machine learning is often thought of as a distant promise. However, in 2017, it has materialized in major ways. Machine learning is at the heart of what makes this year’s iPhone X from Apple and Pixel 2 / XL from Google unique,” Vlad Savov writes for The Verge. “It is the driver of differentiation both today and tomorrow, and the companies that fall behind in it will find themselves desperately out of contention.”

“A machine learning advantage can’t be easily replicated, cloned, or reverse-engineered: to compete with the likes of Apple and Google at this game, you need to have as much computing power and user data as they do (which you probably lack) and as much time as they’ve invested (which you probably don’t have),” Savov writes. “In simple terms, machine learning promises to be the holy grail for giant tech companies that want to scale peaks that smaller rivals can’t reach. It capitalizes on vast resources and user bases, and it keeps getting better with time, so competitors have to keep moving just to stay within reach.”

“Chinese companies may work at ludicrous speeds when iterating on hardware, however the rules change when the thing you’re trying to replicate is months and years of machine learning training,” Savov writes. “The old days of phone makers being able to secure a major hardware advantage for longer than a few months are now gone. At this late stage of the evolution of smartphones, machine learning is the only path toward securing meaningful differentiation.”

Read more in the full article here.

MacDailyNews Take: Owing to the time, money, and expertise required, it will certainly be more difficult, if not downright impossible, for some rambunctious startup to unseat Apple or Google as machine learning begins to power everything from cameras to biometrics and beyond.

Meanwhile, Google has a data advantage in terms of amount of and, perhaps, ability to work with, but also a severe disadvantage when it comes to custom silicon in which Apple wisely began to invest heavily under Steve Jobs and which, under Tim Cook, has only grown in importance and capability (Secure Enclave, Neural Engine, etc.).

SEE ALSO:
Apple explains how ‘Hey Siri’ works using a deep neural network and machine learning – October 19, 2017
How Apple’s machine learning beats Google Android’s – August 22, 2017
Apple launches new Machine Learning website – July 19, 2017
Apple’s Artificial Intelligence Director discusses computers that can remember – March 29, 2017
New hire could be critical step toward attracting high-profile AI research talent to Apple – October 18, 2016
Apple hires a big brain in AI to smarten up Siri – October 17, 2016
Apple transforms Turi into dedicated machine learning division to build future product features – August 31, 2016
An exclusive inside look at how artificial intelligence and machine learning work at Apple – August 24, 2016
Apple rumored to be taking big piece of Seattle-area office market in expansion – August 12, 2016
Why Apple will become a leader in artificial intelligence – August 8, 2016
Apple buys machine-learning startup Turi for $200 million – August 6, 2016
Apple touts Artificial Intelligence in iOS and opens ‘crown jewels’ to developers – June 14, 2016
Smartphones to die out within five years, replaced by artificial intelligence – survey – December 9, 2015
Apple’s extreme secrecy retarding its artificial intelligence work – October 30, 2015
Apple hires NVIDIA’s artificial intelligence director – October 24, 2015
Apple acquires advanced artificial intelligence startup Perceptio – October 5, 2015
Apple buys artificial intelligence natural language start-up VocalIQ – October 2, 2015