An exclusive inside look at how artificial intelligence and machine learning work at Apple

On July 30, 2014, Siri had a brain transplant.

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.

Continue Reading – – https://backchannel.com/an-exclusive-look-at-how-ai-and-machine-learning-work-at-apple-8dbfb131932b#.uvwtwbudj

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