An Exclusive Look at How AI and Machine Learning Work at Apple
Three years earlier, Apple had been the first major tech company to integrate a smart assistant into its operating system. Siri was the company’s adaptation of a standalone app it had purchased, along with the team that created it, in 2010. Initial reviews were ecstatic, but over the next few months and years, users became impatient with its shortcomings. All too often, it erroneously interpreted commands. Tweaks wouldn’t fix it.
So Apple moved Siri voice recognition to a neural-net based system for US users on that late July day (it went worldwide on August 15, 2014.) Some of the previous techniques remained operational — if you’re keeping score at home, this includes “hidden Markov models” — but now the system leverages machine learning techniques, including deep neural networks (DNN), convolutional neural networks, long short-term memory units, gated recurrent units, and n-grams. (Glad you asked.) When users made the upgrade, Siri still looked the same, but now it was supercharged with deep learning.
As is typical with under-the-hood advances that may reveal its thinking to competitors, Apple did not publicize the development. If users noticed, it was only because there were fewer errors. In fact, Apple now says the results in improving accuracy were stunning.
“This was one of those things where the jump was so significant that you do the test again to make sure that somebody didn’t drop a decimal place,” says Eddy Cue, Apple’s senior vice president of internet software and services.
This story of Siri’s transformation, revealed for the first time here, might raise an eyebrow in much of the artificial intelligence world. Not that neural nets improved the system — of course they would do that — but that Apple was so quietly adept at doing it. Until recently, when Apple’s hiring in the AI field has stepped up and the company has made a few high-profile acquisitions, observers have viewed Apple as a laggard in what is shaping up as the most heated competition in the industry: the race to best use those powerful AI tools. Because Apple has always been so tight-lipped about what goes on behind badged doors, the AI cognoscenti didn’t know what Apple was up to in machine learning. “It’s not part of the community,” says Jerry Kaplan, who teaches a course at Stanford on the history of artificial intelligence. “Apple is the NSA of AI.” But AI’s Brahmins figured that if Apple’s efforts were as significant as Google’s or Facebook’s, they would have heard that.