For people who aren't employees, there's usually only one place to buy them or other official Apple swag: the company's headquarters at 1 Infinite Loop.
But once a year there's an exception to that rule. Every year at WWDC, the company's conference for software developers, Apple sets up a company store where attendees can buy Apple merchandise.
With their .mlmodel format, the company is not venturing into the business of training models (at least not yet). Instead, they have rolled out a meticulously crafted red carpet for models that are already trained. It’s a carpet that deploys across their entire lineup of hardware.
As a business strategy, it’s shrewd. As a technical achievement, it’s stunning. It moves complex machine learning technology within reach of the average developer.
"And so, even if they store information in the cloud, it's encrypted with keys that Apple doesn't have. And so [users] can put things in the cloud, they can pull stuff down from the cloud, so the cloud still serves as a conduit—and even ultimately kind of a backup for them—but only they can read it."
It's unclear exactly how Apple is able to pull this off, as there's no explanation of how this works other than from those words by Federighi. The company didn't respond to a request for comment asking for clarifications. It's possible that we won't know the exact technical details until iOS 11 officially comes out later this year.
Tock to tock processor updates don't generally give this kind of performance boost, but the boost is delivered through an increase in RAM speed, the architecture upgrade, and a 300Mhz base clock speed increase.
The double digit CPU gains don't translate over to graphics processing, where we found a modest improvement of 5 percent from 2016 to 2017. Given the flash storage decrease to 128GB, the write speeds are slower there too —but this is to be expected as parallelism decreases with fewer chips.
I want you to take a function in Swift, and I want you to imagine the function as an empty swimming pool. Got it in your mind’s eye? Swimming pool. Empty (for now).
Adam, is an engineer on Google’s self-driving car project (now its own division, called Waymo). He says the daily pace of work borders on fanatical. When he’s in the lab, the outside world disappears—we know this because he tells us so, and also because our text messages and emails to him almost always go unanswered. Adam works full tilt, wholly immersing himself in the brains and guts of a car that, if Google gets it right, will be a total game-changer. Adam, however, would never say that. He knows that he and his team must first figure out, among many other things, how to teach an inanimate object moving at 70 miles per hour to differentiate between a stray plastic bag and a stray deer. Talk about a just-manageable challenge.
Google is built upon projects like the self-driving car: endeavors that push at the point of resistance for growth, where struggle and productive failure aren’t consequences of the work, but rather the driving forces behind it. The company attracts the cream of the crop, top-notch creative thinkers who are passionate about what they do. Add to the mix the tight deadlines and the colleagues who aren’t scared to push the envelope, and it’s easy to see why employees like Adam become so absorbed in their work. Google has nailed the recipe for stress. But the company understands that’s only half the battle. Without rest, Google wouldn’t end up with innovation. Instead, it’d end up with a workforce that is broken down and burnt out.