Tech News

It's been another busy week on the Packt Hub. There has been plenty of interesting stories too from around the world. Here are the highlights from the last 7 days that you might have missed... Tech news Data news AWS Greengrass brings machine learning to the edge [Editor's pick] Is Comet the new Github for Artificial Intelligence? Deeplearning4j 1.0.0-alpha arrives! OpenAI charter puts safety, standards, and transparency first OpenCV 4.0 is on schedule for July release Development & programming news Verizon launches AR Designer, a new tool for developers Windows launches progressive web apps… that don’t yet work on mobile [Editor's pick] Kubernetes 1.10 released Mozilla is building a bridge between Rust and JavaScript What’s new in Visual Studio 1.22? Red Programming Language for Android development! 10 years of GitHub [Editor's pick] Security news Cryptojacking is a growing cybersecurity threat, report warns Vevo’s YouTube account Hacked: Popular videos deleted Other news... Skill Up is back: 5 things we want to find out [Editor's pick] Exciting New Features in C# 8.0 Tutorials Web development tutorials: 7-13 April How to publish Docker and integrate with Maven How to develop RESTful web services in Spring Testing RESTful web services with Postman Applying Spring security using JSON Web Tokens 5 things to consider when developing an eCommerce site Building Docker images using Dockerfiles How to publish a Microservice on Docker Data tutorials: 7-13 April OpenCV Primer: what can you do with Computer Vision and how to get started How greedy algorithms work Get SQL Server management right Recurrent neural networks and the LSTM architecture What is LSTM? [Editor's pick] Understanding SQL Server recovery models to effectively backup and restore your database Image filtering techniques in OpenCV Other... 26 new Java enhancements you will love [Editor's pick] Drones: Everything you ever wanted to know! This week's opinions, analysis and insights Cryptocurrency A brief history of Blockchain Everything you need to know about Ethereum Data GDPR is pushing the Chief Data Officer role center stage [Editor's pick] Amazon Sagemaker makes machine learning on the cloud easy Mark Zuckerberg’s Congressional testimony: 5 things we learned [Editor's pick] Game and mobile development Types of Augmented Reality targets Unity plugins for augmented reality application development

CASL has released a new version 2.0 bringing with it several compelling opportunities for enhancing web app authorization methods. CASL is an isomorphic authorization JavaScript library which allows you to fix user abilities in the system. It grants you to set permissions in order to access the required resources in the system. You need to define the permissions in a single location since you cannot duplicate them across UI components, API services, and database queries. Some of the noteworthy changes available in CASL 2.0 are: Package Refactoring Refactoring is a process of changing a software system to improve the internal structure of the code without altering the external performance.   The lerna project has refactored CASL 2.0 to monorepo. Because of which MongoDB related functionality is moved into a different package, thus decreasing the core library size. You can find the core package at casl/ability and MongoDB related functionality at casl/mongoose, while helper function at casl/ability/extra. You don’t need to worry about updating your dependencies, thanks to renovate bot. CASL procures Frontend frameworks CASL now has complementary packages for leading frontend frameworks such as React, Vue, Angular and Aurelia. You can now integrate CASL into different single page applications with ease.   For more details, you can refer the README file for each library: CASL Vue package CASL React package CASL Angular package CASL Aurelia package Set abilities per fields Now you can set permissions per field of your application. For example if you want certain users with the ability to change the name of the product but not the product description. You can see suitable form fields for different roles in the admin panel Demo Examples If you want demo tutorials as per CASL 2.0 and complementary packages you can visit: Integrate CASL authorization in Vuejs2 application using CASL and Vue Integrate CASL authorization in React application using CASL and React Integrate CASL authorization in Aurelia application using CASL and Aurelia Integrate CASL authorization in Expressjs application using CASL and Expressjs Integrate CASL authorization in Feathersjs application using CASL and Feathersjs If you want to start implementing CASL library in your project or work, you can visit the GitHub page.

It’s been more than 20 years since Microsoft released the first version of the C# language. Over the years C# has experienced a remarkable evolution, from being called as a Java copycat to one of the most loved and used programming languages. The current developments in C# 7 ecosystem are exciting, and grabbing the attention of developers, but what about the future? Can developers take a sneak peek into the future of C#? Well of course they can! The Microsoft language design team have been developing the language features ‘in the open’ for quite some time now. They have proposed several new features for the upcoming C# 8.0 and have released several prototypes for the developers, to try them out and provide feedback on the official Github repo. Let’s take a look at the most likely new C# 8 features: Nullable Reference Types The name of this particular feature might confuse a lot of developers wondering “Isn’t nullable reference a bad idea?” or “Shouldn’t it be called non nullable reference types?”. Sir Tony Hoare, a British computer scientist invented null references and famously called them the “Billion Dollar Mistake” as the biggest problem is, of course, the risk of getting the infamous null-reference exception. Since all reference types in C# can be null, you always run the risk of getting an exception when you try to access some member of the object. Functional languages try to deal with this problem by having a type that represents the concept of potential absent value. Instead of introducing non-nullable reference types in C#, Microsoft has chosen to consider reference types as non-nullable by default and provide mechanisms to deal with nullable types. Since the premise of a reference is often considered to be non-nullable and to be dereferenced. Asynchronous Streams Asynchronous streams provide the ability to use async/await inside an iterator. In most cases, an iterator is implemented synchronously. There are some cases, however, where it might need to await a call on every iteration to fetch the next item. In such cases, asynchronous streams can come in handy. To support this feature, a couple of things need to be taken care of: New types, the async equivalents of IEnumerable and IEnumerator Ability to specify an await on an iterator construct such as foreach. Default interface implementations: The primary use case for default interface methods is to enable the developer to safely evolve an interface. You could add new methods to it and, as long as you provide a default implementation, existing clients of the interface wouldn’t be forced to implement it. Another important value proposition of default implementation on interfaces relates to Android and iOS. Since both Java and Swift offer this feature, it’s tricky to use C# to wrap Android/iOS APIs that make use of default interface implementations. C# 8.0 will make it possible to wrap those APIs more faithfully. There are plenty of other features proposed to be implemented in C# 8 such as target-typed new expressions, covariant return types, and extension everything. All these features are in different stages of development and a lot can (and probably will) change from now until C# 8.0’s release Till then you can closely follow the official Github repo for C#.   Stay up to date with the latest features, release dates, and general discussions on key programming tools and tech by subscribing to Packt Hub. Check out other latest news: Red Programming Language for Android development! What’s new in Visual Studio 1.22 OpenCV 4.0 is on schedule for July release

Technology can change quickly. But it’s also true that some things never change. JavaScript has been the most popular programming language on GitHub since 2012, for example. But whether things shift every month, or things remain constant, it’s important to see what’s actually happening. It helps us develop the content you need to learn. And more importantly, it allows you to better understand the world in which you’re working. That means you can make the right decisions about your professional life. That’s why we’ve launched this year’s Skill Up survey. We want you to tell us what it’s like to be a software developer today. Click here to take the survey now. Read on to find out 5 of the most important things we want we want to find out in this year’s survey: What is the most popular programming language in 2018? According to Stack Overflow’s recent survey report, JavaScript was one of the more popular programming languages, with around 71% of professional developers using JavaScript. We think that this trend will continue and we’ll see JavaScript come out on top along with Python – which has become increasingly popular these past few years. However, you're more than welcome to prove us wrong... How do software developers learn new technical skills? With more than 150,000 developers visiting our online learning platform each week, we think our survey results will show that most developers set aside time each week to learn new technical skills. It will be interesting to see the proportion of developers who spend time each week to that of those who set aside time each month. In their survey report, Stack Overflow found that more than 60% of developers visit Stack overflow almost every day. That signals there's a definite appetite - and need to learn skills and solve new problems. What are the most commonly used tools, libraries, and frameworks? We know how popular the big players such as Node and Angular that make up half of the MEAN stack are so we won’t be surprised to see them coming out on top along with React and TensorFlow. Stack overflow found TensorFlow to be the most loved tool – around 73% of developers expressed a lot of enthusiasm. [box type="note" align="" class="" width=""]Also read about the Top 10 Machine learning tools to watch in 2018![/box] What do developers think will be the most valuable thing to learn this year? We’ve seen Python grow in popularity and JavaScript remains at the number 1 top spot for the most commonly used programming language but what will be the most valuable thing to learn in the next 12 months? Are you a developer? Take part in our survey now and provide valuable insight into the skills, salaries and technology preferences of developers. All responses will remain anonymous. The survey should take no more than 5-10 minutes. You will receive a useful 80% discount to use on any Packt eBook or video of your choice. Next, read our take on the StackOverflow Survey Stack Overflow Developer Survey 2018: A Quick Overview 10 predictable findings from Stack Overflow’s 2018 survey 4 surprising things from Stack Overflow’s 2018 survey

Red has been around for a while now and has been extending its purpose from systems programming to various fields like Blockchain, Android development, among others. Recently, Red introduced some modern implementation support for Android programming. The way Red can be used in Android programming is using a specific bridge, that allows the Red code to call the whole Android API in Java. This allows you to write Android applications in Red language without having to write any Java code. Red, in its latest release, has introduced a new and improved Java bridge for Android. Java bridge was first introduced in Red's version 0.3. With this bridge, the Red programs are able to interface Java Virtual Machine through JNI (Java Native Interface). The new Java bridge now replaces the old implementation and is now optimized for efficient bindings of Red programs to the Android API in Java. This optimization greatly improves the performance of the Android application. To explain this, Red has published a short overview of Red/View backend on Android, the source code for which can be found on this GitHub repo. Red his also been working on implementing several features in its v0.7 release. The community has released a short list of features on its site, though all the work on these features is done in a private repository. The private repo will be opened to selected developers soon for testing and fine-tuning. Some of the features that are set to come in the new release are as follows: Full set of Red/View widgets support Draw & Shape dialects full support Compatibility with Android GUI themes Device-independent coordinate system Updated APK building toolchain for targeting API 23+ Android systems Improved ARM backend, support for ARMv7+ Android support Red has also released a roadmap for the upcoming releases which shows that v0.7 is going to be an important milestone for Android development with Red. Apart from the work in Android, Red has been concentrating on the Blockchain-related wave of tasks, Full I/O, among other high-priority milestones. As of now, Red v0.6.4 has been released on the GitHub repository. The community is still considering a 0.6.5 release, to insert a small extra milestone before going into the 0.7 release. Build your first Android app with Kotlin Why are Android developers switching from Java to Kotlin?

In this ever-growing technology era, one has to ensure the data they put on the internet is in safe hands. No matter which platform you use to share data, there is always a risk of your data being misused. Recently, a group of hackers managed to breach Vevo’s YouTube channel taking down their most-watched videos. This security breach alarmed a lot of viewers as they witnessed something unexpected when searching for popular music videos like ‘Despacito’. The hackers not only took down these videos but also replaced them with a different thumbnail and video title. Apparently, the thumbnail picture used was of a masked gang with guns taken from a Netflix show Casa de Papel and the video title consisted of their nicknames (Prosox and Kuroi’sh). Immediately after this news spread like wildfire, YouTube claimed that it was Vevo that was hacked and not YouTube.  Vevo is owned by the big three record companies in the United States: Warner Music Group, Universal Music Group, and Sony Music Entertainment. Vevo only hosts music videos from artists signed to Sony Music Entertainment and Universal Music Group and those are published on YouTube. YouTube also claimed that there is a big difference between YouTube and Vevo. Anyone with a google account can upload a video to YouTube’s mainstream. But this isn’t the case for Vevo. Vevo is managed by administrators responsible for uploading videos to the website and the Vevo YouTube channel. This means only authorized personnel have access to Vevo’s platform, which is broadcasted on YouTube. This personnel does not have any access to the rest of YouTube overall. It was Vevo’s servers that were hacked as all the affected videos came from that server. Since this attack catered to specific music artists it is still unclear if the hackers got through individual artist accounts or had a wider breakthrough Vevo accounts. So far, only one hacker has claimed that they used scripts to alter video titles. Vevo has already started fixing their security breaches where they have claimed that their affected videos and catalog have been restored to full working order. They are also currently investigating the source of the breach. You can know more about this developing news originally reported by BBC. Check out other latest news: Cryptojacking is a growing cybersecurity threat, report warns Top 5 cloud security threats to look out for in 2018

GitHub celebrated its tenth birthday on Tuesday. Since its launch in April 2008, the version control platform has come to define the way we build software. It's difficult to see open source software culture evolving to the extent it has without GitHub. Its impact can be felt even beyond software. It has changed the ways users experience the web, and it has made artificial intelligence more pervasive than ever. For that reason, we should all pay tribute to GitHub - developers and non-developers alike. You can find Packt on GitHub here. We have more than 1,400 code repositories for our products that you can use as you learn. 27 million developers have 'contributed' to GitHub's success GitHub now has more than 27 million developers on its platform and is home to more than 80 million projects. To say thank you to everyone who has been a part of the last 10 years - everyone who has quite literally contributed to its success - the team put together this short video: https://www.youtube.com/watch?v=hQXV70Z4cFI Key GitHub milestones Let's take a look at some of the most important milestones in GitHub's first decade. Find out more here. April 12, 2008 - GitHub officially launches. Read the post from 2008 to take a trip back in time... May 21, 2009 - Node.js launches and its saga begins. From io.js forking in 2014, to reunification a year later, the JavaScript library is today one of the most popular tools on GitHub. There are almost 2,000 contributors to Node.js Core, the central Node.js project. January 1, 2012 - JavaScript begins 2012 as the most popular language on GitHub. More than 6 years later that still remains the case. January 16, 2013 - GitHub reaches 3 million users. In the space of just 5 year,s the platform was truly embedded in the software landscape. October 23, 2014 - Microsoft takes the significant step of making .NET open source. This was the start of a cultural shift at Microsoft that's still happening today. Perhaps more than any other moment in the history of open source, this underlined the fact that it was no longer a niche stream of the software landscape. It had become part of the mainstream. March 2, 2015 - Unreal Engine 4 makes its source code available for free. This gave game developers access to an incredibly powerful tool for no cost whatsoever. The impact on the growth of game development is important to note. 'Games' was one of the most popular topics on the platform in 2017. December 3, 2015 - Mirroring the move made by Microsoft in 2014, Apple makes Swift open source. Again, this was a huge tech company - with a similar reputation for isolationism - embracing open source. February 15, 2017 - The launch of TensorFlow 1.0 marks the start of the boom in artificial intelligence. Or more specifically, it marks a point at which artificial intelligence and machine learning became accessible to millions more people than ever before. The range of projects that TensorFlow has been a part of is astonishing - from research to medicine to marketing, its accessibility has had an impact on the world in ways that many people don't realise. May 31, 2017 - GitHub's 100 millionth pull request is merged. Thank you, GitHub for 10 years supporting software developers. It really wouldn't have been the same without you. Here's to another 10 years... Is Comet the new Github for Artificial Intelligence? Mine Popular Trends on GitHub using Python – Part 1 Github’s plan for coding automation, TensorFlow releases Tensorflow Lattice – 11th Oct.’ 17 Headlines Collaboration Using the GitHub Workflow Using Gerrit with GitHub

Cryptojacking is a growing threat to users, a UK cyber security agency warns. In its Cyber Threat to UK Business report, the UK's National Cyber Security Centre (NCSC), outlines the growing use of cryptojacking as a method of mining bitcoin by stealth. The report quotes an earlier study by Checkpoint, done at the end of 2017, indicating that 55% of businesses globally had been impacted by the technique. One of the most interesting aspects of cryptojacking is how it's blurring the lines of cybercriminality. Although the NCSC 'assumes' that it is ultimately a new technique being used by experienced cyber criminals, the report also notes that websites - without necessarily having any record of cybercrime - are using it as a way of mining cryptocurrencies without users' knowledge. It's worth noting that back in February, Salon gave users the option to supress ads in return for using their computing power. This was essentially a legitimate and transparent form of cryptocurrency mining. What is cryptojacking? Cryptojacking is a method whereby a website visitor's CPU is 'hijacked' by a piece of JavaScript code that runs when the user accesses a specific webpage. This code then allows cybercriminals to 'mine' cryptocurrencies (at present Monero) without users' knowledge. The NCSC report gives an example of this in action. According to the report, more than 4,000 websites "mined cryptocurrency through a compromised screen-reading plugin for blind and partially sighted people." Cryptojacking looks set, then, to become a larger problem within the cybersecurity world. Because it's so hard for users to identify that they are being exploited, it's likely that this will be difficult to tackle. However, technology savvy users are already creating solutions to protect from cryptojacking. This will effectively become the next wave of ad blockers. It will be interesting to see whether this does, in fact, become a model that the media industry takes on to tackle struggling revenues. Could Salon's trial lead to the increased adoption of legitimate cryptojacking as a revenue stream? Whatever happens, user consent is going to remain an issue. Source: Coindesk Vevo’s YouTube account Hacked: Popular videos deleted Top 5 cloud security threats to look out for in 2018

Ready Players. One Two Three! We begin with the epic battle between the two most prominent game engines out there: Unity vs Unreal Engine. Unreal Engine has been surviving for the past 20 years, the legacy engine while Unity, relatively new, (although it’s almost 12 years) is nevertheless an equal champion. We will be evaluating these engines across 6 major factors. Without further ado, let the games begin. Unity vs Unreal Engine Performance Performance is a salient factor when it comes to evaluating a game engine’s performance. The Unreal Engine uses C++. C++ is a lower level programming language that provides developers with more control over memory management. On top of this, Unreal Engine gives developers full access to the C++ source code allowing editing and upgrading anything in the system. Unity, on the other hand, uses C#, where the memory management is out of a developer’s control. No control over memory signifies that the garbage collector can trigger at random time and ruin performance. Unreal offers an impressive range of visual effects and graphical features. More importantly, they require no external plugins (unlike Unity) to create powerful FX, terrain, cinematics, gameplay logic, animation graphs, etc. However, UE4 seems to perform various basic actions considerably slower. Actions such as starting the engine, opening the editor, opening a project, saving projects, etc take a lot of time hampering the development process. Here’s where Unity takes the edge. It is also the go-to game engine when it comes to creating mobile games. Considering the above factors we can say, in terms of sheer performance, Unreal 4 takes the lead over Unity. But Unity may be making up for this shortfall by being more in sync with the times i.e., great for creating mobile games, impressive plugins for AR etc. Also read about Unity 2D and 3D game kits to simplify game development for beginners. Learning curve and Ease of development Unity provides an exhaustive list of resources to learn from. These documentations are packed with complete descriptions complemented with a number of examples as well as video and text tutorials and live training sessions. Along with the official Unity resources, there are also high-quality third-party tutorials available. The Unreal Engine offers developers a free development license and source code but for 5% royalty. The Unreal Engine 4 has Blueprint visual scripting. These tools are designed for non-programmers and designers to create games without writing a single line of code. They feature a better-at-glance game logic creation process, where flowcharts with connections between them are used for representing the program flow. These flowcharts make games a lot faster to prototype and execute. Unity offers an Asset store for developers to help them with all aspects of design. It features a mix of animation and rigging tools, GUI generators and motion capture software. It also has powerful asset management and attributes inspection. Unity is generally seen as the more intuitive and easier to grasp game engine. Unreal Engine features a simplistic UI that doesn’t take long to get up and running. With this, we can say, that both Unity and Unreal are at par in terms of ease of use. Unity vs Unreal Engine Graphics When it comes to graphics, Unreal Engine 4 is a giant. It includes capabilities to create high-quality 2D and 3D games with state-of-the-art techniques such as particle simulations systems, deferred shading, lit translucency, post-processing features and advanced dynamic lighting. Unity is also not far behind with features such as static batching, physically-based shading, shuriken particle system, low-level rendering access etc.  Although Unreal engine comes out to be the clear winner, if you don't need to create next-gen level graphics then having something like Unreal Engine 4 may not be required, and hence Unity wins. Platform Support/compatibility Unity is a clear winner when it comes to the number of platforms supported. Here’s a list of platforms offered by both Unity and Unreal. Platform Unreal Unity iOS Available Available Android Available Available VR Available Available (also HoloLens) Linux Available Available Windows PC Available Available Mac OS X Available Available SteamOS Available Available HTML5 Available Not Available Xbox One Available Available (also Xbox 360) PS4 Available Available Windows Phone 8 Not Available Available Tizen Not Available Available Android TV and Samsung Smart TV Not Available Available Web Player Not Available Available WebGL Not Available Available PlayStation Vita Not Available Available Community Support Community support is an essential criterion for evaluating a tool’s performance, especially true for free tools. Both Unity and Unreal have large and active communities. Forums and other community sources have friendly members that are quick to respond and help out. Having said that, a larger community of game developers contribute to Unity’s asset store. This saves significant time and effort, as developers can pick out special effects, sprites, animations, etc directly from the store rather than developing them from scratch. Correspondingly, more developers share tutorials and offer tech support on Unity. Unity vs Unreal Engine Pricing Unity offers a completely free version ready for download. This is a great option if you are new to game development.  The Unity Pro version, which offers additional tools and capabilities (such as the Unity profiler) comes at $1,500 as a one-time charge, or $75/month. Unreal Engine 4, on the other hand, is completely free. There are no Pro or Free versions. However, Unreal Engine 4 has a royalty fee of 5% on resulting revenue if it exceeds $3000 per quarter. Unreal Engine 4 is also completely free for colleges and universities, although the 5% royalty is still attached. Both game engines are extremely affordable, Unity gives you access to the free version, which is still a powerful engine. Unreal Engine 4 is of course completely free. The verdict The above analysis favors Unreal as the preferred gaming engine. In reality, though, it all boils down to the game developer. Choosing the right engine really depends on the type of game you want to create, your audience, and your expertise level (such as your choice of programming language). Both these engines are evolving and changing at a rapid pace and it is for the developer to decide where they want to head. Also, check out: Unity Machine Learning Agents: Transforming Games with Artificial Intelligence Unity plugins for augmented reality application development Unity releases ML-Agents v0.3: Imitation Learning, Memory-Enhanced Agents and more

Microsoft has released the latest version of Visual Studio 1.22 recently with a few additions and improvements to it. The primary feature that Microsoft has introduced is called “Logpoints”. The idea of Logpoints is very literal - i.e. these are the breakpoints while debugging code and while taking note of these breakpoints, the developers need not stop code execution and can keep a track of events. The primary changes are: Syntax Aware code folding: This feature allows better code folding for CSS, HTML, JSON and Markdown files. This feature ensures that the code folding is not based on indentation but based on code syntax and hence makes the code much more readable and developer friendly. Conversion to ES6 Refactoring: How many times have you thought that a little bit of help while coding would have made your coding experience better? Visual Studio has added this feature in their new release. The code suggest button (an elliptical hover button) will suggest latest ES 6 code snippets and the developers will have the choice to accept it or modify it. A welcome feature for the new and mid-level programmers for sure. Auto Attach to process: This feature provides a lot of help for the Node.js developers. It automatically starts debugging node.js programs and applications the moment you launch them, eliminating the need for a dedicated launcher program. The other important features of the new version are: Cross file error, warning and reference navigation: This helps you to navigate through the different workspaces efficiently. Improved Large File support: This enables faster syntax highlighting and helps in better and larger memory allocation for bigger applications making the overall debugging process faster. Multi-Line links in the terminal: This feature allows developers to hyperlink multiple links spanning across several lines in the editor. Better organization of JavaScript/TypeScript imports: This feature helps programmers to remove unused codes and sort their imports in a more orderly manner. Emmet Wrap preview: This feature provides the live preview for Emmet's wrap with abbreviation functionality. With these new and exciting features, Visual Studio surely is moving towards a more user-friendly and predictive coding platform for the programmers. We will keep a close watch on its future release and share updates on how these releases target better code reusability, importing different codes easily and better-debugging functionality. Read about the full update on the official Visual Studio website. C++, SFML, Visual Studio, and Starting the first game  

There has been some exciting news from OpenCV: OpenCV developer Vadim Pisarevsky announced the development on OpenCV 4 on the GitHub repository of OpenCV and addressed why the time is right for the release of OpenCV 4. OpenCV 3 was released in 2015 taking 6 years to come out after OpenCV 2 which was released in 2009. OpenCV 3 has been built around C++ 98 standards. Re-writing the library in the recent version of C++ like C++ 11 or later versions would mean to break the "binary compatibility". This makes it important to move further from the OpenCV 3 promises. There are two interesting concepts that we need to know here - Binary compatibility and source-level compatibility. OpenCV had made a promise to stay binary-compatible with versions, that means the release of new OpenCV versions will stay compatible with the previous version library calls. Now moving from C++ 98 standard to recent C++ standard will break this promise. However, OpenCV has looked into this and found that not much harm will be caused by this migration, hence relaxing the "binary compatibility" and moving to "source compatibility" with the new release. Apart from migrating to latest C++ standards, the OpenCV library needs refactoring and new module additions for Deep learning and neural networks seeing the heavy usage of OpenCV in machine learning. OpenCV developers can expect some big revisions in functions and modules. Here is a quick summary of what you might expect in this major release of OpenCV 4.0: Hardware-accelerated Video I/O module: This module maximizes OpenCV performance using software and hardware accelerator in the machine. This means calling this module with OpenCV 4 will harness the acceleration. HighGUI module (Revised): With the enhancement of this module, you can efficiently read video from camera or files and also perform a write operation on them. This module comes with a lot of functionality for media IO operation. Graph API module: This module creates support for efficiently reading and writing graphs from the image. Point Cloud module: Point cloud module contains algorithms such as feature estimation, model fitting, and segmentation. These algorithms can be used for filtering noisy data, stitch 3D point clouds, segment part of the image, among others. Tracking, Calibration, and Stereo Modules, among other features that will benefit image processing with OpenCV. You can find the full list of a new module that might get added in OpenCV 4 in the issues page of OpenCV repo. The OpenCV community is relying on its huge developer community to facilitate closing the open issues within the speculated time of release, that is July 2018. Functionalities that don’t make it OpenCV 4 release, will be rolled into the OpenCV 4.x releases. While you wait for OpenCV 4, enjoy these OpenCV 3 tutorials: New functionality in OpenCV 3.0 Fingerprint detection using OpenCV 3 OpenCV Primer: What can you do with Computer Vision and how to get started? Image filtering techniques in OpenCV Building a classification system with logistic regression in OpenCV Exploring Structure from Motion Using OpenCV

OpenAI, the non-profit that promotes the development of artificial intelligence, has released a charter. In it, the organization outlines the core principles it believes should govern the development and management of artificial intelligence. The OpenAI charter represents an important step in initiating a broader discussion around the ethical considerations of artificial intelligence. Revealed in a short blog post, the organization explains that the OpenAI charter is a summation of the development of its strategy over the last two years. Its mission remains central to the charter, however: ensuring that the development of artificial intelligence benefits all of humanity.  What's inside the OpenAI charter? The charter is then broken down into 4 other areas. Broadly-distributed benefits - OpenAI claims its primary duty is to humanity Long-term safety Technical leadership - OpenAI places itself at the cutting edge of the technology that will drive AI forward Cooperative orientation - working with policy-makers and institutions Core concerns the OpenAI charter aims to address A number of core concerns lie at the heart of the charter. One of the most prominent is what OpenAI see as the competitive race to create AGI "without time for adequate safety precautions". It's because of this that OpenAI seeks cooperation with "other research and policy institutions" - essentially ensuring that AI doesn't become a secretive corporate arms race. Clearly, for OpenAI, transparency will be key to creating artificial intelligence that is 'safe'. OpenAI also claims it will publish its most recent AI research. But perhaps even more interestingly, the charter goes on to say that "we expect that safety and security concerns will reduce our traditional publishing in the future, while increasing the importance of sharing safety, policy, and standards research." There appears to be a tacit recognition of a tension between innovation of AI and the ethics around such innovations. A question nevertheless remains over how easy it is for an organization to be at the cutting-edge of AI technology, while taking part in conversations around safety and ethics. As the last decade of technical development has proved, innovation and standards sometimes seem to be diametrically opposed, rather than in support of one another. This might be important in moving beyond that apparent opposition. 'If tech is building the future, let’s make that future inclusive and representative of all of society’ – An interview with Charlotte Jee What your organization needs to know about GDPR 20 lessons on bias in machine learning systems by Kate Crawford at NIPS 2017 Mark Zuckerberg’s Congressional testimony: 5 things we learned The Cambridge Analytica scandal and ethics in data science

Mozilla is building a bridge between Rust and JavaScript. The bridge - Wasm-bindgen - allows Rust to interact with Web Assembly modules and JavaScript. One of Mozilla's aims is to turn Rust into a language for web development; building a link to WebAssembly is perhaps the most straightforward way for it to run on the web. But this doesn't mean Mozilla wants Rust to replace JavaScript - far from it. The plan is instead for Rust to be a language that runs alongside JavaScript on the backend. Read more about Mozilla's plan here. What is wasm-bindgen? It's worth reading this from the Mozilla blog to see the logic behind wasm-bidgen and how it's going to work: "Today the WebAssembly specification only defines four types: two integer types and two floating-point types. Most of the time, however, JS and Rust developers are working with much richer types! For example, JS developers often interact with document to add or modify HTML nodes, while Rust developers work with types like Result for error handling, and almost all programmers work with strings. Being limited only to the types that WebAssembly provides today would be far too restrictive, and this is where wasm-bindgen comes into the picture. The goal of wasm-bindgen is to provide a bridge between the types of JS and Rust. It allows JS to call a Rust API with a string, or a Rust function to catch a JS exception. wasm-bindgen erases the impedance mismatch between WebAssembly and JavaScript, ensuring that JavaScript can invoke WebAssembly functions efficiently and without boilerplate, and that WebAssembly can do the same with JavaScript functions." This is exciting as it is a valuable step in expanding the capabilities of Rust. But the thinking behind wasm-bindgen will also help to further drive the adoption of web assembly. While the focus is, of course, on Rust at the moment, there's a possibility that wasm-bindgen could eventually be used with other languages, such as C and C++. This might take some time, owever. Download wasm-bindgen from GitHub.

In an effort to sync their releases with Kubernetes, RedHat skipped 3.8 release and came up with version 3.9, for their very own container application platform i.e OpenShift. RedHat seems to be moving really quick with their OpenShift roadmap, with 3.10 release lined up in Q2 2018 (June). The primary takeaway from the accelerated release cycle of OpenShift is the importance of the tool in RedHat DevOps expansion. With dedicated support to cutting-edge tools like Docker and Kubernetes, OpenShift looks like a strong DevOps tool, which is here to stay. The OpenShift 3.9 release has quite a few exciting middleware updates, bug fixes, and service extensions. Let’s look at some of the enhancements in key areas:   Container Orchestration OpenShift has added Soft Image Pruning, wherein you don't have to remove the actual image, but need to just update the etcd storage file instead. Added support to deploy RedHat ClouForms on OpenShift container engine. Added features: OpenShift Container Platform template provisioning Offline OpenScapScans Alert management: You can choose Prometheus (currently in Technology Preview) and use it in CloudForms. Reporting enhancements Provider updates Chargeback enhancements UX enhancements The inclusion of CRI-O V1.9, a lightweight native Kubernetes run-time interface. Addition of CRI-O brings the following advancements: A minimal and secure architecture. Excellent scale and performance. The ability to run any Open Container Initiative (OCI) or docker image. Familiar operational tooling and commands. Storage Expand persistent volume claims online from {product-tile} for CNS glusterFS, Cinder, and GCE PD. CNS deployments are automated and CNS Un-install Playbook is added with the release of OpenShift 3.9 Developer Experience Improvements in Jenkins support, which intelligently predicts to pod memory before processing it. Updated CLI-plugins or binary extensions, which extends the default set of OC commands, allowing you to perform a new task. The BUILDCONFIG DEFAULTER now allows specifications now allows a toleration value, which is applied upon creation. For minor bug fixes and the complete release data, refer to  OpenShift Release Notes.  

The Skymind team has announced a milestone release of Eclipse Deeplearning4j (DL4J), an open-source library for deep learning. DL4J 1.0.0-alpha has some breakthrough changes which will ease development of deep learning applications using Java and Scala. From a developer’s perspective, the roadmap provides an exciting opportunity to perform complex numerical computations with the major updates done to each module of Deeplearning4j. DL4J is a distributed neural network library in Java and Scala which allows distributed training on Hadoop and Spark. It provides powerful data processing that enables efficient use of CPUs and GPUs. With new features, bug fixes and optimizations in the toolkit, Deeplearning4j provides excellent capabilities to perform advanced deep learning tasks. Here are some of the significant changes available in DL4J 1.0.0-alpha: Deeplearning4j: New changes made to the framework Enhanced and new layers added to the DL4J toolkit. Lots of new API changes to optimize the training, building, and deploying neural network models in the production environment. A considerable amount of bug fixes and optimizations are done to the DL4J toolkit. Keras 2 import support Now you can import Keras 2 models into DL4J, while still keeping backward compatibility for Keras 1. The older module DL4J-keras and Model API in DL4J version 0.9.1 is removed. In order to import Keras models, the only entry point you can use is KerasModelImport.   Refer DL4J-Keras import support to know more about the complete list of updates. ND4J: New features A powerful library used for scientific and numerical computing for the JVM: Hundreds of new operations and features added to ease scientific computing, an essential building block for deep learning tasks. Added NVIDIA CUDA support for 9.0/9.1. They are continuing support for CUDA 8.0, however dropping support for CUDA 7.5. New API changes are done to the ND4J library. ND4J: SameDiff There is a new Alpha release of SameDiff, which is an auto-differentiation engine for ND4J. It supports two execution modes for serialized graphs: Java-driven execution, and Native execution. It also supports import of TensorFlow and ONNX graphs for inference purposes. You can know all the other new features at SameDiff release notes. DataVec: New features An effective ETL library for getting data into the pipeline, so neural networks can understand: Added new features and bug fixes to perform efficient and powerful ETL processes. New API changes incorporated in the DataVec library. Arbiter: New features A package for efficient optimization of neural networks to obtain good performance: New Workspace support added to carry out hyperparameter optimization of machine learning models. New layers and API changes have been done to the tool. Bug fixes and improvements for optimized tuning performances. A complete list of changes is available on Arbiter release notes. RL4J: New features A reinforcement learning framework integrated with deeplearning4j for the JVM: Added support for LSTM layers to asynchronous advantage actor-critic (A3C) models. Now you can use the latest version of VizDoom since MDP for Doom is updated. Lots of fixes and improvements implemented in the RL4J framework. ScalNet A scala wrapper for DL4J resembling a Keras like API for deep learning: New ScalNet Scala API is released which is very much similar to Keras API. It supports Keras based sequential models. The project module closely resembles both DL4J model-import module and Keras. Refer ScalNet release notes, if you like to know more. ND4S: N-Dimensional Arrays for Scala An open-source Scala bindings for ND4J: ND4S now has Scala 2.12 support Possible issues with the DL4J 1.0.0-alpha release Since this is an alpha release, you may encounter performance related issues and other possible issues (when compared to DL4J version 0.9.1). This will be addressed and rectified in the next release. Support for training a Keras model in DL4J is still very limited. This issue will be handled in the next release. To know more, you can refer Keras import bug report. Major new operations added in ND4J still do not use GPU yet. The same applies to the new auto-differentiation engine for ND4J. We can expect more improvements and new features on DL4J 1.0.0 roadmap. For the full list of updates, you can refer the release notes.  Check out other popular posts: Top 6 Java Machine Learning/Deep Learning frameworks you can’t miss Top 10 Deep learning frameworks