We start with some developer news of the week, then dig into the best bits from WWDC.
Plus Mike shares his thoughts on some new hardware & the guys discuss the mystery of differential privacy.
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— Show Notes: —
New app preview launch. Try it out while in Beta for a 25% off discount: https://t.co/bLkpTDG7IU
Checkout GitMasque!@ChrisLAS #Mac— Michael Dominick (@dominucco) June 13, 2016
Hoopla
- Faster App Review Times
- Subscription Model
- Apple’s App Store now has over 2 million apps
macOS Sierra (“Tabs everywhere”)
- Continuity
- Auto unlock – Tied to a device like the watch.
- Universal clipboard
- Optimized storage: Moves older files to the cloud. Auto clean up scripts. Takes on AppleJacks and other Mac tools.
- Apple Pay on the web. Supports Touch ID on the iPhone.
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Apple heard you like Tabs…
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New file system spotted in macOS Sierra [Updated] | Ars Technica
Swift Playgrounds
Introduced as a new way for children to learn how to code, Apple will bring its Swift programming language to iPad with Swift Playground, a touch-friendly way for beginners to grasp the basics.
“Swift Playgrounds will revolutionize the way people learn to code.”
“Combining the powerful Swift programming language and the powerful capabilities of iPad.”
“We believe coding should be a required language in all schools. Swift Playground will be free.”
Swift Playgrounds = the new HyperCard?
— John Gruber (@gruber) June 13, 2016
iOS 10 (“The mother of all releases”)
- Apple Beta Software Program
- iOS 10
- New lock screen, expanded notifications, interactive notifications.
- Google Now like today screen filled with 3rd party widgets.
- Siri gets an API: Apple opens up Siri to app developers
- Siri built into Calendar events, looks ups, multilingual typing on the fly.
- Photos: Advanced Computer Vision. Face finding, done local. Object recognition. Works across devices to bring moments together
- Caller ID API
- Voip apps get integration with call/lock screen and contacts app
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iMessage Apps (SDK)
In cryptography, differential privacy aims to provide means to maximize the accuracy of queries from statistical databases while minimizing the chances of identifying its records.
Differential privacy formalizes the idea that a “private” computation should not reveal whether any one person participated in the input or not, much less what their data are.