All posts on August, 2017


Oracle doesn’t want Java EE any more

Oracle wants to end its leadership in the development of enterprise Java and is looking for an open source foundation to take on the role.

The company said today that the upcoming Java EE (Enterprise Edition) 8 presents an opportunity to rethink how the platform is developed. Although development is done via open source with community participation, the current Oracle-led process is not seen agile, flexible, or open enough. ”We believe that moving Java EE technologies to an open source foundation may be the right next step, to adopt more agile processes, implement more flexible licensing and change the governance process,” Oracle said in a statement.

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Online Entertainment

Report: Apple to Funnel Megabucks Into Original TV Content Development

Apple reportedly has decided to put more than $1 billion toward the acquisition and development of original programming, part of a long-awaited rollout of a new television and film experience. The investment will leverage Apple’s thus far underwhelming Apple TV business, bolstering its core video and music library to fulfill the promise of disrupting traditional television and film studios.

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What features to expect in Apple’s Swift 5

Version 5 of Apple’s Swift language used for iOS and MacOS application development will arrive in late 2018 with ABI (application binary interface) stability in the standard Swift library a primary focus—delaying a feature originally intended for the upcoming Swift 4 release.

Locking down the ABI iin Swift 5 will mean any future compiler versions can produce binaries that conform to the stable ABI. “Once an ABI is stable, it tends to persist for the rest of the platform’s lifetime due to ever-increasing mutual dependencies,” according to Apple documentation.

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13 frameworks for mastering machine learning

13 frameworks for mastering machine learning
13 frameworks for mastering machine learning

Image by W.Rebel via Wikimedia

Over the past year, machine learning has gone mainstream with a bang. The “sudden” arrival of machine learning isn’t fueled by cheap cloud environments and ever more powerful GPU hardware alone. It is also due to an explosion of open source frameworks designed to abstract away the hardest parts of machine learning and make its techniques available to a broad class of developers.

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Enterprise Security

The War Room: Experiential Security Planning

Ask any security practitioner about ransomware nowadays, and chances are good you’ll get an earful. Recent outbreaks like Petya and WannaCry have left organizations around the world reeling, and statistics show that ransomware is on the rise. For example, 62 percent of participants surveyed for ISACA’s recent “Global State of Cybersecurity” survey experienced a ransomware attack in 2016.

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The most popular IDEs? Visual Studio and Eclipse

Microsoft’s Visual Studio leads the way in desktop IDE (integrated development environment) popularity, with Eclipse close behind, according to PYPL’s August index of IDE popularity. Android Studio was a distant third.

Visual Studio takes a 22.4 percent share in this month’s index. Eclipse follows with a 20.38 percent share. Much further back was Android Studio, with a 9.87 percent share. “It’s surprising how a couple of IDEs have about half the popularity,” PYPL’s Pierre Carbonelle said.

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Tech Buzz

Gadget Ogling: Trending Hot Plates, Toys for Future Coders, and a Ringy Dingy Ring

If you’ve looked at Facebook for more than a minute over the last few years, there’s no question that you’ll have encountered a top-down, perfectly filmed food video from BuzzFeed’s Tasty channel. The cooking clips are enormously popular on the social network, racking up billions of views a month. Now BuzzFeed is trying to monetize its success in a new way. Enter the Tasty One Top, a hot plate that seeks to make cooking simpler.

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Docker Enterprise now runs Windows and Linux in one cluster

With the newest Docker Enterprise Edition, you can now have Docker clusters composed of nodes running different operating systems.

Three of the key OSes supported by Docker—Windows, Linux, and IBM System Z—can run applications side by side in the same cluster, all orchestrated by a common mechanism.

Clustering apps across multiple OSes in Docker requires that you build per-OS images for each app. But those apps, when running on both Windows and Linux, can be linked to run in concert via Docker’s overlay networking.

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Oracle’s Hurd, AT&T’s Donovan on their massive cloud migration deal

If worries about digital transformation projects keep you up at night, imagine how it would feel to be responsible for moving thousands of internal databases to the cloud for a company with more than $160 billion in annual sales and 260,000 employees. That’s the job that AT&T Communications CEO John Donovan is undertaking, and he’s working with Oracle CEO Mark Hurd to do it. 

When the companies announced in May that they were working together, Hurd called the agreement “historic.” While hyperbole is part of everyday life in tech, lessons learned from the massive project are bound to reverberate across enterprises in a variety of fields, as Hurd noted in the following discussion with Donovan and IDG News Service Editor in Chief Marc Ferranti.

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Google’s Deeplearn.js brings machine learning to the browser

Google is offering an open source, hardware-accelerated library for machine learning that runs in a browser. The library is currently supported only in the desktop version of Google Chrome, but the project is working to support more devices. 

The Deeplearn.js library enables training of neural networks within a browser, requiring no software installation or back end. “A client-side ML library can be a platform for interactive explanations, for rapid prototyping and visualization, and even for offline computation,” Google researchers said. “And if nothing else, the browser is one of the world’s most popular programming platforms.”

Using the WebGL JavaScript API for 2D and 3D graphics, Deeplearn.js  can conduct computations on the GPU. This offers significant performance, thus getting past the speed limits of JavaScript, the researchers said.

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AWS unveils AI monitoring for Amazon S3

AWS launched Amazon Macie today, a service that leverages machine learning to help customers prevent inadvertent exposure of sensitive data and unauthorized access to data in Amazon S3. The company said Amazon Macie will support additional AWS storage services later this year. 

Inside the company’s S3 (Simple Cloud Storage Service) platform, Amazon Macie will use natural language processing to discover and classify sensitive data, looking at factors such as personally identifiable information, private keys, and credit card information. The Macie service will also continuously monitor data access for unusual activity. Anomalies will trigger alerts to a customer’s security team, Matt Wood, general manager of artificial intelligence at AWS, said.

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Microsoft unveils simpler .Net Core, standard .Net APIs

Microsoft’s .Net Core 2.0, an upgrade to the company’s open source, cross-platform implementation of .Net, is becoming available today. The new release includes improvements intended to make .Net Core easier to use. It also conforms to the .Net Standard 2.0 specification designed to facilitate code sharing among .Net Framework, .Net Core, and Xamarin.

The .Net Core framework can be used to build web applications and services that run on Windows, MacOS, or Linux. Ease of use improvements in .Net Core 2.0 include making the dotnet restore command (used to install project dependencies and other tasks) implicit for commands like run, build, and publish that require it.

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GitHub’s Atom editor gets a speed boost

GitHub has just released an upgrade to its “hackable” Atom text editor, adding a native C++ buffer and rewriting the DOM interaction layer. The company also has offered a glimpse of the next version, which will improve Git integration and PHP support.

With this week’s Atom 1.19 release, a native C++ text buffer boosts responsiveness and memory usage. “Saving a file now happens asynchronously without blocking the UI, so that you can move smoothly from one task to the next,” GitHub’s Ian Olsen said. Also, large files now consume less memory.

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Amazon joins Kubernetes-focused CNCF industry group

The Cloud Native Computing Foundation, created to promote and develop technologies like Kubernetes and core components of the container ecosystem spawned by Docker, welcomed Amazon Web Services into its fold this week.

Amazon comes on board as a top-level (“platinum”) member. According to Amazon’s Adrian Cockcroft, now a member of the CNCF’s governing board, containers are the big reason Amazon’s getting involved—at least, initially.

Amazon already has a major investment in container tech. Its ECS service provides managed containers that run via machine images deployed on clusters of EC2 instances. Its older Elastic Beanstalk service can deploy and manage Docker containers, although they’re scaled and managed via Amazon’s own internal stack, not the CNCF’s Kubernetes. And users can always manually deploy Docker Enterprise Edition, a container-centric Linux such as CoreOS, or a Kubernetes cluster on EC2.

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What is machine learning? Software derived from data

You’ve probably encountered the term “machine learning” more than a few times lately. Often used interchangeably with artificial intelligence, machine learning is in fact a subset of AI, both of which can trace their roots to MIT in the late 1950s.

Machine learning is something you probably encounter every day, whether you know it or not. The Siri and Alexa voice assistants, Facebook’s and Microsoft’s facial recognition, Amazon and Netflix recommendations, the technology that keeps self-driving cars from crashing into things – all are a result of advances in machine learning.

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Google releases TensorFlow Serving library

Google has just moved to a production release of TensorFlow Serving, its open source library for serving machine-learned models in production environments. A beta version of the technology was released in February.

Part of Google’s TensorFlow machine intelligence project, the TensorFlow Serving 1.0 library is intended to aid the deployment of algorithms and experiments while maintaining the same server architecture and APIs. TensoFlow Serving lets you push out multiple versions of models over time, as well as roll them back.

The library of course integrates with TensorFlow learning models, but it can also be extended to serve other model types.

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IBM speeds deep learning by using multiple servers

For everyone frustrated by how long it takes to train deep learning models, IBM has some good news: It has unveiled a way to automatically split deep-learning training jobs across multiple physical servers — not just individual GPUs, but whole systems with their own separate sets of GPUs.

Now the bad news: It’s available only in IBM’s PowerAI 4.0 software package, which runs exclusively on IBM’s own OpenPower hardware systems.

Distributed Deep Learning (DDL) doesn’t require developers to learn an entirely new deep learning framework. It repackages several common frameworks for machine learning: TensorFlow, Torch, Caffe, Chainer, and Theano. Deep learning projecs that use those frameworks can then run in parallel across multiple hardware nodes.

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How Google’s Go language could be improved

To improve development tools for Google’s open source Go language, Go might be getting its own language server, akin to Microsoft and Red Hat’s Language Server Protocol.

The notion came up in a Go language contributors’ discussion group, so it’s not a done deal.

The group’s consensus recommendations are:

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IBM speeds deep learning by using multiple servers

For everyone frustrated by how long it takes to train deep learning models, IBM has some good news: It has unveiled a way to automatically split deep-learning training jobs across multiple physical servers — not just individual GPUs, but whole systems with their own separate sets of GPUs.

Now the bad news: It’s available only in IBM’s PowerAI 4.0 software package, which runs exclusively on IBM’s own OpenPower hardware systems.

Distributed Deep Learning (DDL) doesn’t require developers to learn an entirely new deep learning framework. It repackages several common frameworks for machine learning: TensorFlow, Torch, Caffe, Chainer, and Theano. Deep learning projecs that use those frameworks can then run in parallel across multiple hardware nodes.

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JetBrains ships alternative to Microsoft’s Visual Studio

JetBrains’s Rider, a cross-platform IDE that could serve as a rival to Microsoft’s own well-established Visual Studio IDE, is now generally available.

The commercially licensed Rider can be used on Windows, MacOS, and Linux systems, letting developers build applications based on ASP.Net, .Net Core, .Net Framework, Xamarin, or Unity. Rider puts JetBrains’ ReSharper .Net support in the shell of the company’s IntelliJ Idea IDE and adds the WebStorm JavaScript IDE and DataGrip database management tool. ReSharper previously was packaged as a Visual Studio extension for code analysis and instant fixes.

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Java and C hit all-time lows in Tiobe language popularity index

Java and C continue to lead the Tiobe index of programming language popularity, but both dropped to all-time lows in the just-published August release of the index.

The longtime leaders have had to share the programming landscape with a growing number of language options attracting developers, which has caused their slippage in the index. Java’s rating this month was 12.961 percent, a drop of more than six percentage points since August 2016, while C’s rating was 6.477 percent, a year-over-year drop of nearly five points. Java’s rating last month was 13.774 percent while C was rated at 7.321 percent.

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What’s new in Angular 5: easier progressive web apps

Angular, Google’s popular JavaScript framework for building mobile and desktop applications, has had a whirlwind year, with two major upgrades in the past 11 months. It will reach the next milestone in its six-month release schedule in September, when Angular 5 is due to debut with major accommodations for Google-driven progressive web apps.

Despite the “5” designation, the upgrade will actually be just the fourth release for the framework, which already has undergone a rewrite since the 1.0 version, initially called AngularJS, debuted in 2012. Angular 5 is now in beta release and is scheduled for production release on September 18.

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React ‘Fiber’ core rewrite progresses to beta

React 16, an upgrade to Facebook’s popular JavaScript UI library that features a rewritten core to improve animation, layout, and gesture support, has just moved to a beta release stage.

Published as an NPM module, this initial beta release is focused mainly on compatibility with existing apps, and does not yet include asynchronous rendering capabilities. Facebook has pledged to offer native-like performance with version 16 of the open source library. Previously codenamed “Fiber,” the rewritten core is intended to offer a multitude of capabilities including:

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New Node.js API will shield modules from JavaScript engine changes

Help is on the way for developers building native modules for Node.js, as well for those who want to swap out the underlying JavaScript engine powering the platform.

Currently, modules must be recompiled to work with new versions of Node.js and the JavaScript engine, which traditionally has been Google’s V8 engine. But N-API is about to make things easier by providing an API for linking in native add-ons. Independent of the underlying JavaScript runtime, N-API will be stable for the application binary interface (ABI) across Node versions, to insulate add-ons from changes in the underlying JavaScript engine. Modules compiled for one version of Node.js would then run on later versions with no need to recompile.

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