Good Reads for August, 2016

Originally published at: http://appletalk.com.au/2016/09/good-reads-for-august-2016/
Every month, we’ll be bringing you a handful of enthusiastically endorsed — if slightly longer — reads about the wonderful world of Apple. Sometimes these will be interviews with Apple executives, other times they’ll be deep dives into how Apple’s artificial intelligence and machine learning is making a difference in the day-to-day of millions. Bring your own Instapaper account or other preferred read-it-later service, because this is Good Reads.

  • August was apparently the month for interviews, and Fast Company led the charge with their piece on Tim Cook's Apple. It just so happens that August 2016 happens to mark Cook's fifth year at the helm of one of the biggest companies in the world, and Fast Company's interview with the Apple CEO paints the picture of a leader who has to constantly face the music on every facet of Apple.
But, in the five years under Cook, Apple’s revenue has tripled, its workforce has doubled, and its global reach has expanded rapidly. [...] Cook has shown a great capacity for getting improvements from every corner of the company, and for then deploying those gains across a wider canvas of software, hardware, and services than Jobs ever had at his disposal. He will never be as flashy as Jobs, but he may just be the perfect CEO for the behemoth Apple has become.
  • A separate profile of Apple CEO Tim Cook from the Washington Post opens with the headline that running Apple "is sort of a lonely job". But alongside with not asking for sympathy as CEO, Cook also has thoughts on where Apple has been, and where Apple is going. Despite Apple's financials looking worse than they have for a while, Cook remains optimistic about both the global technology market and Apple's prospects.
As CEO, he gets high marks for managing the company’s growth, keeping margins high and expanding further into markets such as China (Apple had four retail stores in China five years ago. Today it has 41.) He has pushed into the enterprise market, grown Apple’s product lineup and positioned Apple to make more money off the devices it’s already sold: Its services business, which includes things like iTunes, iCloud and a mobile payments service, is projected to be the size of a Fortune 100 business next year — all on its own. Apple remains the most valuable and most profitable company in the S&P 500 index.
  • Also from Fast Company is an interview with perhaps the other top two at Apple. In their interview, Apple veterans Eddy Cue and Craig Federighi talk about learning from Apple's failures, number one of which seems to be Apple's own maps project. While everyone is expecting Apple to come out with a revolutionary breakthrough product, Apple is instead playing the game of experiences — meaningful interactions, like the one in macOS Sierra that will allow you to unlock your Mac with your Apple Watch.
We make mistakes, things get out there, but we work incredibly hard to make things better and better. The bar does keep going up. The number of things you expect from your phone and your computer and the way they interact, and the cloud and services and the way the Internet works with them, the level of complexity goes up and up. But we’re committed to getting better and better, faster than it gets harder and harder.
  • Over at Medium, Steven Levy takes a look behind the scenes at how artificial intelligence and machine learning work at Apple. Siri's transformations July 2014 for US users and in August 2015 for everyone else flew completely under-the-radar, but represented a change from what Siri used to use to a neural net model. The change was tiny, but represented a massive leap forward both in Siri's recognition accuracy and how quietly adept Apple was at machine learning and AI.
Yet as the briefing unfolds, it becomes clear how much AI has already shaped the overall experience of using the Apple ecosystem. The view from the AI establishment is that Apple is constrained by its lack of a search engine (which can deliver the data that helps to train neural networks) and its inflexible insistence on protecting user information (which potentially denies Apple data it otherwise might use). But it turns out that Apple has figured out how to jump both those hurdles.
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