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Apple’s Sidecar just really *gets* me, you know? – TechCrunch

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With the rollout of Apple’s public beta software previews of macOS and the new iPadOS, I’ve finally been able to experience first-hand Sidecar, the feature that lets you use an iPad as an external display for your Mac. This is something I’ve been looking to make work since the day the iPad was released, and it’s finally here – and just about everything you could ask for.

These are beta software products, and I’ve definitely encountered a few bugs including my main Mac display blanking out and requiring a restart (that’s totally fine – betas by definition aren’t fully baked). But Sidecar is already a game-changer, and one that I will probably have a hard time living without in future – especially on the road.

Falling nicely into the ‘it just works’ Apple ethos, setting up Sidecar is incredibly simple. As long as your Mac is running macOS 10.15 Catalina, and your iPad is nearby, with Bluetooth and Wifi enabled, and running the iPadOS 13 beta, you just click on the AirPlay icon in your Mac’s Menu bar and it should show up as a display option.

Once you select your iPad, Sidecar just quickly displays an extended desktop from your Mac on the iOS device. It’s treated as a true external display in macOS System Preferences, so you can arrange it with other displays, mirror your Mac and more. The one thing you can’t do that you can do with traditional displays is change the resolution – Apple keeps things default here at 1366 x 1024, but it’s your iPad’s extremely useful native resolution (2732 x 2048, plus Retina pixel doubling for the first-generation 12.9-inch iPad Pro I’m using for testing), and it means there’s nothing weird going on with pixelated graphics or funky text.

Apple also turns on, by default, both a virtual Touchbar and a new feature called ‘Sidebar’ (yes, it’s a Sidebar for your Sidecar) that provides a number of useful commands including the ability to call up the dock, summon a virtual keyboard, quickly access the command key and more. This is particularly useful if you’re using the iPad on its own without the attached Mac, which can really come in handy when you’re deep in a drawing application and just looking to do quick things like undo, and Apple has a dedicated button in Sidebar for that, too.

The Touchbar is identical to Apple’s hardware Touchbar, which it includes on MacBook Pros, dating back to its introduction in 2016. The Touchbar has always been kind of a ‘meh’ feature, and some critics vocally prefer the entry-level 13-inch MacBook Pro model that does away with it altogether in favor of an actual hardware Escape key. And on the iPad using Sidecar, you also don’t get what might be its best feature – TouchID. But, if you’re using Sidecar specifically for photo or video editing, it’s amazing to be able to have it called up and sitting there ready to do, as an app-specific dedicated quick action toolbar.

Best of all, Apple made it possible to easily turn off both these features, and to do so quickly right from your Mac’s menu bar. That way, you get the full benefit of your big beautiful iPad display. Sidecar will remember this preference too for next time you connect.

Also new to macOS Catalina is a hover-over menu for the default window controls (those three ‘stoplight’ circular buttons that appear at the top left of any Mac app). Apple now provides options to either go fullscreen, tile your app left or right to take up 50% of your display, or, if you’re using Sidecar, to quickly move the app to Sidecar display or back.

This quick shuffle action works great, and also respects your existing windows settings, so you can move an app window that you’ve resized manually to take up a quarter of your Mac’s display, and then when you send it back from the Sidecar iPad, it’ll return to where you had it originally in the same size and position. It’s definitely a nice step up in terms of native support for managing windows across multiple displays.

I’ve been using Sidecar wirelessly, though it also works wired and Apple has said there shouldn’t really be any performance disparity regardless of which way you go. So far, the wireless mode has exceeded all expectations, and any third-party competitors in terms of reliability and quality. It also works with the iPad Pro keyboard case, which makes for a fantastic input alternative if you happen to be closer to that one instead of the keyboard you’re using with your Mac.

Sidecar also really shines for digital artists, because it supports input via Apple Pencil immediately in apps that have already built in support for stylus input on Macs, including Adobe Photoshop and Affinity Photo. I’ve previously used a Wacom Cintiq 13HD with my Mac for this kind of thing, and I found Apple’s Sidecar to be an amazing alternative, not least of which because it’s wireless and even the 12.9 iPad Pro is such more portable than the Wacom device. Input seems to have very little response lag (like, it’s not even really perceivable), there’s no calibration required to make sure the Pencil lines up with the cursor on the screen, and as I mentioned above, combined with the Sidebar and dedicated ‘Undo’ button, it’s an artistic productivity machine.

The Pencil is the only means of touch input available with Sidecar, and that’s potentially going to be weird for users of other third-party display extender apps, most of which support full touch input for the extended Mac display they provide. Apple has intentionally left out finger-based touch input, because Mac just wasn’t designed for it, and in use that actually tracks with what my brain expects, so it probably won’t be too disorienting for most users.

When Apple introduced the 5K iMac, it left out one thing that had long been a mainstay of that all-in-on desktop – Target Display Mode. It was a sad day for people who like to maximize the life of their older devices. But they’ve more than made up for it with the introduction of Sidecar, which genuinely doubles the utility value of any modern iPad, provided you’re someone for whom additional screen real estate, with or without pressure-sensitive pen input, is something valuable. As someone who often works on the road and out of the office, Sidecar seems like something I personally designed in the room with Apple’s engineering team.

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Apple and Google’s AI wizardry promises privacy—at a cost

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Since the dawn of the iPhone, many of the smarts in smartphones have come from elsewhere: the corporate computers known as the cloud. Mobile apps sent user data cloudward for useful tasks like transcribing speech or suggesting message replies. Now Apple and Google say smartphones are smart enough to do some crucial and sensitive machine learning tasks like those on their own.

At Apple’s WWDC event this month, the company said its virtual assistant Siri will transcribe speech without tapping the cloud in some languages on recent and future iPhones and iPads. During its own I/O developer event last month, Google said the latest version of its Android operating system has a feature dedicated to secure, on-device processing of sensitive data, called the Private Compute Core. Its initial uses include powering the version of the company’s Smart Reply feature built into its mobile keyboard that can suggest responses to incoming messages.

Apple and Google both say on-device machine learning offers more privacy and snappier apps. Not transmitting personal data cuts the risk of exposure and saves time spent waiting for data to traverse the internet. At the same time, keeping data on devices aligns with the tech giants’ long-term interest in keeping consumers bound into their ecosystems. People that hear their data can be processed more privately might become more willing to agree to share more data.

The companies’ recent promotion of on-device machine learning comes after years of work on technology to constrain the data their clouds can “see.”

In 2014, Google started gathering some data on Chrome browser usage through a technique called differential privacy, which adds noise to harvested data in ways that restrict what those samples reveal about individuals. Apple has used the technique on data gathered from phones to inform emoji and typing predictions and for web browsing data.

More recently, both companies have adopted a technology called federated learning. It allows a cloud-based machine learning system to be updated without scooping in raw data; instead, individual devices process data locally and share only digested updates. As with differential privacy, the companies have discussed using federated learning only in limited cases. Google has used the technique to keep its mobile typing predictions up to date with language trends; Apple has published research on using it to update speech recognition models.

Rachel Cummings, an assistant professor at Columbia who has previously consulted on privacy for Apple, says the rapid shift to do some machine learning on phones has been striking. “It’s incredibly rare to see something going from the first conception to being deployed at scale in so few years,” she says.

That progress has required not just advances in computer science but for companies to take on the practical challenges of processing data on devices owned by consumers. Google has said that its federated learning system only taps users’ devices when they are plugged in, idle, and on a free internet connection. The technique was enabled in part by improvements in the power of mobile processors.

Beefier mobile hardware also contributed to Google’s 2019 announcement that voice recognition for its virtual assistant on Pixel devices would be wholly on-device, free from the crutch of the cloud. Apple’s new on-device voice recognition for Siri, announced at WWDC this month, will use the “neural engine” the company added to its mobile processorsto power up machine learning algorithms.

The technical feats are impressive. It’s debatable how much they will meaningfully change users’ relationship with tech giants.

Presenters at Apple’s WWDC said Siri’s new design was a “major update to privacy” that addressed the risk associated with accidentally transmitting audio to the cloud, saying that was users’ largest privacy concern about voice assistants. Some Siri commands—such as setting timers—can be recognized wholly locally, making for a speedy response. Yet in many cases transcribed commands to Siri—presumably including from accidental recordings—will be sent to Apple servers for software to decode and respond. Siri voice transcription will still be cloud-based for HomePod smart speakers commonly installed in bedrooms and kitchens, where accidental recording can be more concerning.

Google also promotes on-device data processing as a privacy win and has signaled it will expand the practice. The company expects partners such as Samsung that use its Android operating system to adopt the new Privacy Compute Core and use it for features that rely on sensitive data.

Google has also made local analysis of browsing data a feature of its proposal for reinventing online ad targeting, dubbed FLoC and claimed to be more private. Academics and some rival tech companies have said the design is likely to help Google consolidate its dominance of online ads by making targeting more difficult for other companies.

Michael Veale, a lecturer in digital rights at University College London, says on-device data processing can be a good thing but adds that the way tech companies promote it shows they are primarily motivated by a desire to keep people tied into lucrative digital ecosystems.

“Privacy gets confused with keeping data confidential, but it’s also about limiting power,” says Veale. “If you’re a big tech company and manage to reframe privacy as only confidentiality of data, that allows you to continue business as normal and gives you license to operate.”

A Google spokesperson said the company “builds for privacy everywhere computing happens” and that data sent to the Private Compute Core for processing “needs to be tied to user value.” Apple did not respond to a request for comment.

Cummings of Columbia says new privacy techniques and the way companies market them add complexity to the trade-offs of digital life. Over recent years, as machine learning has become more widely deployed, tech companies have steadily expanded the range of data they collect and analyze. There is evidence some consumers misunderstand the privacy protections trumpeted by tech giants.

A forthcoming survey study from Cummings and collaborators at Boston University and the Max Planck Institute showed descriptions of differential privacy drawn from tech companies, media, and academics to 675 Americans. Hearing about the technique made people about twice as likely to report they would be willing to share data. But there was evidence that descriptions of differential privacy’s benefits also encouraged unrealistic expectations. One-fifth of respondents expected their data to be protected against law enforcement searches, something differential privacy does not do. Apple’s and Google’s latest proclamations about on-device data processing may bring new opportunities for misunderstandings.

This story originally appeared on wired.com.

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Amazon joins Apple, Google by reducing its app store cut

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Enlarge / The Amazon Fire HD 8 tablet, which runs Amazon’s Fire OS.

Apparently following the lead of Apple and Google, Amazon has announced that it will take a smaller revenue cut from apps developed by teams earning less than $1 million annually from their apps on the Amazon Appstore. The same applies to developers who are brand-new to the marketplace.

The new program from Amazon, called the Amazon Appstore Small Business Accelerator Program, launches in Q4 of this year, and it will reduce the cut Amazon takes from app revenue, which was previously 30 percent. (Developers making over $1 million annually will continue to pay the original rate.) For some, it’s a slightly worse deal than Apple’s or Google’s, and for others, it’s better.

Amazon’s new indie-friendly rate is 20 percent, in contrast to Apple’s and Google’s 15 percent. Amazon seeks to offset this difference by granting developers 10 percent of their Appstore revenue in the form of a credit for AWS. For certain developers who use AWS, it could mean that Amazon’s effective cut is actually 10 percent, not 15 or 20 percent.

But for some, it amounts to something more like giving the developer a coupon on a purchase of services from Amazon than actually putting more cash in their pockets. It leaves small developers who aren’t spending a bunch of money on Amazon’s services with a worse deal than they’d get on Apple’s or Google’s marketplaces.

As with Apple’s program—but not Google’s—the lower rate applies to developers only if they made $1 million or less in total (in this case, the numbers assessed are those from the previous year). Crossing that threshold will lead developers to pay the older, higher rate on all of their earnings. In contrast, Google always takes a smaller cut of the first million in a given year and then applies the bigger cut to revenues after $1 million without changing the amount it took from the first million.

The Amazon Appstore primarily exists as the app store for Amazon’s Android-based Fire OS software that runs on tablets. It’s also offered as an alternative App Store for users of other Android-based operating systems.

All three companies are facing various forms of regulatory scrutiny, and that scrutiny was likely a factor in Apple’s decision to cut the fees it applies to apps released by small developers on the Apple App Store. Google followed shortly afterward for its Google Play marketplace.

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Microsoft’s Linux repositories were down for 18+ hours

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Enlarge / In 2017, Tux was sad that he had a Microsoft logo on his chest. In 2021, he’s mostly sad that Microsoft’s repositories were down for most of a day.

Jim Salter

Yesterday, packages.microsoft.com—the repository from which Microsoft serves software installers for Linux distributions including CentOS, Debian, Fedora, OpenSUSE, and more—went down hard, and it stayed down for around 18 hours. The outage impacted users trying to install .NET Core, Microsoft Teams, Microsoft SQL Server for Linux (yes, that’s a thing) and more—as well as Azure’s own devops pipelines.

We first became aware of the problem Wednesday evening when we saw 404 errors in the output of apt update on an Ubuntu workstation with Microsoft Teams installed. The outage is somewhat better documented at this .NET Core-issue report on Github, with many users from all around the world sharing their experiences and theories.

The short version is, the entire repository cluster which serves all Linux packages for Microsoft was completely down—issuing a range of HTTP 404 (content not found) and 500 (Internal Server Error) messages for any URL—for roughly 18 hours. Microsoft engineer Rahul Bhandari confirmed the outage roughly five hours after it was initially reported, with a cryptic comment about the infrastructure team “running into some space issues.”

Eighteen hours after the issue was reported, Bhandari reported that the mirrors were once again available—although with temporarily degraded performance, likely due to cold caches. In this update, Bhandari said that the original cause of the outage was “a regression in [apt repositories] during some feature migration work that resulted in those packages becoming unavailable on the mirrors.”

We’re still waiting for a comprehensive incident report, since Bhandari’s status updates provide clues but no real explanations. The good news is, we can confirm that packages.microsoft.com is indeed up once again, and it is serving packages as it should.

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