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Intel and Google plot out closer collaboration around Chromebooks and the future of computing – TechCrunch

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Intel, the chip-making giant, has been on the road of refocusing its strategy in recent months. While it has sold its mobile chip operation to Apple and is reportedly looking for a buyer for its connected home division, it’s also been going through the difficult task of rethinking how best to tackle the longtime bread and butter of its business, the PC.

Part of that latter strategy is getting a big boost this week at CES 2020. Here, Intel is today announcing a deeper partnership with Google to design chips and specifications for Chromebooks built on Project Athena. Project Athena is framework first announced last year that covers both design and technical specs, with the aim of building the high-performance laptops of tomorrow that can be used not just for work, but media streaming, gaming, enterprise applications and more, all on the go — powered by Intel, naturally.

(The specs include things like requiring ‘fast wake’ using fingerprints or push-buttons or lift lids; using Intel Core i5 or i7 processors; “Ice Lake” processor designs; better battery life and charging; WiFi 6; touch displays; 2-in-1 designs; narrow bezels and more.)

Earlier today, the first two Chromebooks built on those Athena specifications — from Samsung and Asus — were announced by the respective companies, and Intel says that there will be more to come. And on stage, Google joined Intel during its keynote to also cement the two companies’ commitment to the mission.

“We’re going a step further and deepening our partnership with Google to bring Athena to Chromebooks,” Gregory Bryant, the EVP and GM of Intel’s client computing group, said in an interview with TechCrunch ahead of today. “We’ve collaborated very closely with Google [so that device makers] can take advantage of these specs.”

For Intel, having a Chromebook roster using Athena is important because these have been very popular, and it brings its processors into machines used by people who are buying Chromebooks to get access to Google services around security and more, and its apps ecosystem.

But stepping up the specifications for Chromebooks is as important for Google as it is for Intel in terms of the bottom line and growing business.

“This is a significant change for Google,” said John Solomon, Google’s VP of ChromeOS, in an interview ahead of today. “Chromebooks were successful in the education sector initially, but in the next 18 months to two years, our plan is to go broader, expanding to consumer and enterprise users. Those users have greater expectations and a broader idea of how to use these devices. That puts the onus on us to deliver more performance.”

The renewed effort comes at an interesting time. The laptop market is in a generally tight spot these days. Overall, the personal computing market is in a state of decline, and forecast to continue that way for the next several years.

But there is a slightly brighter picture for the kinds of machines that are coming out of collaborations like the one between Intel, Google, and their hardware partners: IDC forecasts that 2-in-1 devices — by which it means convertible PCs and detachable tablets — and ultra-slim notebook PCs “are expected to grow 5% collectively over the same period,” versus a compound annual growth rate of -2.4% between 2019 and 2023. So there is growth, but not a huge amount.

Up against that is the strength of the smartphone market. Granted, it, too, is facing some issues as multiple markets reach smartphone saturation and consumers are slower to upgrade.

All that is to say that there are challenges. And that is why Intel, whose fortunes are so closely linked to those of personal computing devices since it makes the processors for them, has to make a big push around projects like Athena.

Up to this month, all of the laptops built to Athena specs have been Windows PCs — 25 to date — but Intel had always said from the start Chromebooks would be part of the mix, to help bring the total number of Athena-based devices up to 75 by the end of this year (adding 50 in 2020).

Chromebooks are a good area for Intel to be focusing on, as they seem to be outpacing growth for the wider market, despite some notable drawbacks about how Chrome OS has been conceived as a “light” operating system with few native tools and integrations in favor of apps. IDC said that in Q4 of 2019, growth was 19% year-on-year,  and from what I understand the holiday period saw an even stronger rise. In the US, Chromebooks had a market share of around 27% last November, according to NPD/Gfk.

What’s interesting is the collaborative approach that Intel — and Google — are taking to grow. The Apple -style model is to build vertical integration into its hardware business to ensure a disciplined and unified approach to form and function: the specifications of the hardware are there specifically to handle the kinds of services that Apple itself envisions to work on its devices, and in turn, it hands down very specific requirements to third parties to work on those devices when they are not services and apps native to Apple itself.

While Google is not in the business of building laptops or processors (yet?), and Intel is also far from building more than just processors, what the two have created here is an attempt at bringing a kind of disciplined specification that mimics what you might get in a vertically integrated business.

“It’s all about building the best products and delivering the best experience,” Bryant said.

“We can’t do what we do without Intel’s help and this close engineering collaboration over the last 18 months,” Solomon added. “This is the beginning of more to come in this space, with innovation that hasn’t previously been seen.”

Indeed, going forward, interestingly Bryant and Solomon wouldn’t rule out that Athena and their collaboration might extend beyond laptops.

“Our job is to make the PC great. If we give consumers value and a reason to buy a PC we can keep the PC alive,” said Bryant, but he added that Intel is continuing to evolve the specification, too.

“From a form factor you’ll see an expansion of devices that have dual displays or have diff kinds of technology and form factors,” he said. “Our intention is to expand and do variations on what we have shown today.”

CES 2020 coverage - TechCrunch



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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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