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Looks like Christmas has come early this year!  After the latest iPhone range announced by Apple, Amazon’s wide range of Alex products that even included a voice-activated microwave, Microsoft unveiled a host of devices ahead of the holiday shopping season. With a vision to empower people and organizations to achieve more, Microsoft's tools focus on life experiences as a whole. To manage the emerging digital lifestyle, they have been delivering technology that empowers users rather than overwhelm them. The lineup of announcements includes a new version of its desktop computer, called the Surface Studio 2, and its first pair of smart headphones. It also announced the Surface Pro 6 and Surface Laptop 2. Let’s take a brief look at these devices: #1 Surface Pro 6 Surface Pro 6 is 67% faster than its predecessor with an Intel 8th Gen Quad Core processor. With ultimate portable mobility, this device offers hassle-free connectivity, uncompromising mobility, and exceptional power and performance. With an all day battery, full friction hinge, 12.3” PixelSense Display and multi-screen docking to present content beautifully, Surface Pro 6 is something to watch out for! Source: Microsoft #2 Surface Laptop 2 This ultra-light, fast-charging laptop has been beautifully designed and crafted. It gets supercharged with Intel 8th Gen Quad Core Processor, while offering up to 14.5 hours of battery life with faster and quieter typing. The 13.5” PixelSense Display screen offers an immersive touchscreen for faster, more natural navigation Source: Microsoft   #3 Surface Studio 2 As compared to its predecessor, Surface Studio 2 has 50% more graphics performance. With a 28” PixelSense Display, the gadget offers USB-C support and Xbox Wireless built-in gaming-class performance. It includes the latest Surface Pen with tilt sensibility and 4096 levels of pressure. Source: Microsoft #4 Surface Headphones This is Microsoft’s first premium and smart headphone includes a smarter way to listen, with rich audio and hands-free calling. With adjustable noise cancellation and automatic pause and play, Microsoft is aiming to change the way users listen to music! Source: Microsoft #5 Surface All Access Surface All Access offers the option of paying monthly for the Surface products and starts at just $24.99 per month for 24 months. This comes with an Office 365 subscription, access to in-store training and top-tier support. Other Windows 10 & Office 365 Announcements 1. Your Phone App The Your Phone App helps users access their texts and photos in their Android phone to their PC. This ensures users maintain their focus while working on a PC as pausing a task on their PC to respond to a text or notification on your phone can break focus. 2. Windows Timeline on Phone To combat the challenging issue of finding files and documents or web pages accessed throughout the day across different devices, Windows Timeline enables a user to scroll back in time and find the files and websites they were using across their devices. 3. To-Do Integration with Outlook.com & Skype The To-Do integration with Outlook.com, drags tasks into an open slot on a user’s calendar and blocks time to complete it. In Skype, users need to select the message and tap “Create a task” to open the tasks pane.They can then add, edit, and check off tasks. Tasks will be saved and available in Skype, or in the To-Do app. 4. Family Safety for Microsoft Launcher With Microsoft Launcher installed and a Microsoft family group of accounts set up on a family’s Android devices, parents can stay up to date on their kids’ location to ensure their safety. Parents can check in on kids’ app activity on their Android device, including which apps are accessed and the time spent on each app. 5. Inking in PowerPoint Powerpoint users can now transform an inked bulleted list into perfectly formatted text. While inking a flow chart or diagram, users can design their slide using ink, and Designer will use AI to recommend slides to choose from. 6. Inking in Word The Ink Editor, allows users to add a word, split words or add new lines to their document without touching a keyboard. They can edit a Word document from start to finish using their digital pen and touch-enabled device. 7. Embedded 3D Animations In PowerPoint and Word, dynamically animated movements are built into 3D objects. This makes it effortless to incorporate 3D and animation into a user’s project. Surface All Access is already available at Microsoft retail stores in the U.S. The rest of the products are expected to launch by the end of this year. To know more, you can visit Microsoft's official page. Microsoft Ignite 2018: New Azure announcements you need to know Neural Network Intelligence: Microsoft’s open source automated machine learning toolkit Microsoft’s new neural text-to-speech service lets machines speak like people  

At the 33rd conference of the Association for the Advancement of Artificial Intelligence (AAAI), Amazon Alexa researchers in collaboration with researchers from University of Texas will be presenting a paper that describes a new method for compressing neural networks which will, in turn, increase the performance of the network. Yesterday, on the Amazon Blog, Anish Acharya and Rahul Goel, both applied scientists at Amazon Alexa AI, explained how huge neural networks tend to slow down the performance of a system. The proposed paper called ‘"Online Embedding Compression for Text Classification using Low Rank Matrix Factorization”, includes a method to compress embedding tables that often compromises the NLU network’s performance thus slowing down AI based systems like Alexa. This will help Alexa perform more and more complex tasks in milliseconds. The researchers covered the following topics within the paper: A compression method for deep NLP models to reduce the memory footprint using low-rank matrix factorization of the embedding layer. This lead to accuracy through further fine tuning. They depicted that their method outperformed baselines like fixed-point quantization and offline embedding compression for sentence classification. They provide an analysis of inference time for their method Introduce CALR, a novel learning rate scheduling algorithm for gradient descent based optimization. They further depicted how CALR outperformed other popular adaptive learning rate algorithms on sentence classification. Steps taken to obtain optimal performance of the Network The blog lists in short, the steps taken by the researchers to compress the neural network: A set of pre trained word embeddings called ‘Glove’ was used for this experiment. Glove takes into consideration a words co-occurrence in huge bodies of training data and assesses words’ meanings. The team started with a model initialized with large embedding space, performed a low rank projection of the embedding layer using Singular Value Decomposition (SVD) and continuing training to regain any lost accuracy. The aim of the experiment was integrating the embedding table into the neural network to use task-specific training data. This would not only to fine-tune the embeddings but also customize the compression scheme as well. SVD was used to reduce the embeddings’ dimensionality. This broke down their initial embedding matrix into two smaller embedding matrices with a reduction of parameters to almost 90%. One of these matrices poses as one layer of a neural network and the second matrix as the layer above it. Between the layers are connections with associated “weights.” which can be readjusted by the training process. These determine how much influence the outputs of the lower layer have on the computations performed by the higher one. The paper describes a new procedure for selecting the network’s “learning rate”. They vary the ‘cyclical learning rate’ procedure to  escape the local minima condition that gets introduced. This technique is called the cyclically annealed learning rate, which gives better performance than either the cyclical learning rate or a fixed learning rate. Results and conclusion The system developed by the researchers could shrink a neural network by 90 percent for both LSTM and DAN models, while reducing its accuracy by less than 1%. They compared their model to two alternatives. One in which the embedding table is compressed before network training begins and the other is simple quantization, in which all of the values in the embedding vector are rounded to a limited number of reference values. On testing their approach across a range of compression rates, on different types of neural networks, using different data sets, they found that their system outperformed the other approaches used in the experiment. You can read the research paper for more details on the experiments and acquired results. Researchers build a deep neural network that can detect and classify arrhythmias with cardiologist-level accuracy Researchers design ‘AnonPrint’ for safer QR-code mobile payment: ACSC 2018 Conference Researchers introduce a machine learning model where the learning cannot be proved  

The team at GitLab is now considering to move towards a single Rails repository by combining the two existing repositories. Although the GitLab Community Edition code would remain open source and MIT licensed and also the GitLab Enterprise Edition code would remain source available and proprietary. The challenges with having two repositories? The Ruby on Rails code of GitLab is currently maintained in two repositories. The gitlab-ce repository for the code with an open source license and the gitlab-ee repository for code with a proprietary license which is source available. Having two similar but separate repositories, can make feature development difficult and error-prone while making any change in GitLab. To demonstrate the problem, the team at GitLab has given a few examples: Duplicated work during feature development The frontend only Merge Request needed a backport to CE repository. Backporting requires creating duplicate work in order to avoid future conflicts and changes to the code to support the feature. A simple change can break master A minor change in CE repository failed the pipeline in the master branch. Conflicts during preparation for regular releases There might be conflicts during preparation for a regular release, e.g. 11.7.5 release. Merge requests for both the CE repository and EE repository need to be created. And when the pipelines pass, the EE repository would require a merge from the CE repository. This would cause additional conflicts, pipeline failures, and similar delays during which the CE distribution release also would get delayed. Steps taken by GitLab team to improve the situation Before 2016, merging the CE repository into the EE repository was done when the team was ready to cut a release and the number of commits was small so it could be done by one person. As the number of commits between the two repositories grew in 2016, so the task got divided between seven developers who were responsible for merging the code once a day. This worked fine for some time until delays started happening due to failed specs or difficult merge conflicts. The team then merged an MR that allowed the creation of automated MRs between the two repositories by the end of 2017. This task ran every three hours, which allowed for a smaller number of commits to be worked on. The number of changes going into CE and EE repositories grew to thousands of commits in some cases by the end of 2018. This made the automated MR insufficient. The Merge Train tool was then created to automate these workflows further and which automatically rejected merge conflicts and preferred changes from one repository over the other. What is the GitLab team proposing? The gitlab-ce distribution package consists of gitlab-ce repository which offers only the Core feature set.  The gitlab-ee distribution package consists of gitlab-ee repository. The change which the team is considering proposing would be to merge the gitlab-ce and gitlab-ee repositories into a single gitlab repository. The design for merging two codebases requires the work and process changes in detail. Though the proposed change would pertain only to the Ruby on Rails repository. Expected changes The gitlab-ce and gitlab-ee repositories may be replaced with a gitlab repository, with all open issues and merge requests moved into the single repository. All frontend assets such as JavaScript, CSS, images, views will be open sourced under the MIT license. The proprietary backend code will be located in the /ee repository. All the documentation that will be merged together will now clearly state which features belong to which feature set. The downsides The GitLab team was clear about the possible downsides of this approach: Users with installations from the source are currently cloning the gitlab-ce repository. The clone will also fetch the proprietary code in /ee directory. The database migration code is open source and does not require additional maintenance so there is no additional work required. The team is now exploring better ways to solve the problem of busy work and plans to bring improvements to the current proposal. To know more about this news, check out the post by GitLab. Introducing GitLab Serverless to deploy cloud-agnostic serverless functions and applications GitLab 11.7 releases with multi-level child epics, API integration with Kubernetes, search filter box and more Why moving from a monolithic architecture to microservices is so hard, Gitlab’s Jason Plum breaks it down [KubeCon+CNC Talk]

Today, MariaDB Corp. announced that it has acquired a San Francisco-based database company, Clustrix. With this acquisition, MariaDB plans to add a scale-out capability that runs on-premises with commodity hardware or in any cloud environment. This, in turn, will provide greater scalability and higher availability than other traditional distributed options such as Oracle RAC. MariaDB is an adaptable solution because of its architecture that supports pluggable and purpose-built storage engines. Clustrix is a provider of relational database engineered for cloud and datacenter. Known for the scalability it provides, the ClustrixDB is an ideal database solution for high-transaction, high-value applications. How will Clustrix acquisition benefit MariaDB? Michael Howard, CEO, MariaDB Corporation, says, “With Clustrix, MariaDB can provide a better solution for our customers that have challenging scale-out enterprise environments. Our distributed solution will satisfy the most extreme requirements of our largest customers and gives them the freedom to break from Oracle’s lock-in.” The company believes that the acquisition of Clustrix will allow MariaDB Labs to tackle the challenges in the database field. These challenges are extreme in distributed computing, machine learning, next-generation chips, and memory and storage environments. Both Clustrix and MariaDB share the same vocabulary and work on similar problems. Also, both aim to be compatible with MySQL. This makes Clustrix a good fit for MariaDB. Howard says, “the database was always built to accommodate external database storage engines. MariaDB will have to make some changes to its APIs to be ready for the clustering features of Clustrix. It’s not going to be a 1-2-3 effort, it’s going to be a heavy-duty effort for us to do this right. But everyone on the team wants to do it because it’s good for the company and our customers.” This simply means integrating the Clustrix database technology into MariaDB won’t be trivial. To know more about this acquisition in detail, visit MariaDB blog MariaDB 10.3.7 releases Building a Web Application with PHP and MariaDB – Introduction to caching Installing MariaDB on Windows and Mac OS X

Microsoft’s kicked off Build 2018, their annual developer conference in style, with some interesting announcements related to coupling their existing products - mainly Microsoft Azure - with trending technologies such as Artificial Intelligence, IoT, Blockchain, and more. Held in Seattle, Washington over 7th and 8th May, this tech extravaganza promises to give away some exciting insights into Microsoft’s strategy for the coming year. Here is a quick recap of all the major announcements from Day 1: Azure IoT Edge open-sourced Microsoft open-sourced its Azure IoT Edge Runtime platform for their developers, in a bid to deliver cloud intelligence across all their IoT devices. Combining the power of Artificial Intelligence and the Azure services through this platform, Microsoft plans to connect over 20 billion devices globally by 2020. Microsoft also announced their partnership with Qualcomm to create smart camera-based IoT solutions, by combining the hardware from the Qualcomm Vision Intelligence Platform and the Azure services. They will also be teaming up with the China-based drone giants DJI to build a new drone SDK for Windows 10. Azure will be the official cloud solution for DJI’s commercial solutions which will utilize the AI services offered by Microsoft to analyze data for their customers. Last but not the least, Microsoft announced the first Azure Cognitive Service for the edge. Using this feature, the developers will be able to deploy AI algorithms to build powerful applications that run on these devices. Kinect returns - this time on Azure The Kinect is back! This time however, things are a bit different. Built on a technology that also runs the Microsoft Hololens, Kinect will now run on Azure rather than on the Xbox. This new and improved project will have a next-gen camera and a dedicated processor designed to handle the AI tasks to process significant amount of data before it is put up on the Azure cloud. It is worth remembering that Microsoft had also attempted to bring Kinect to the enterprise, way back in 2011, but the project failed miserably and was suspended in 2017. With a different approach this time, Microsoft are hoping to make this a resounding success. New Blockchain tools for Azure In a bid to simplify Blockchain app development on the cloud, Microsoft has announced a new Azure service called Azure Blockchain Workbench. This service will connect the decentralized applications to the Azure cloud services such as Azure Active Directory, and will dramatically reduce the overall development time. This workbench will equip Blockchain developers with all the necessary tools to develop end-to-end Azure-based Blockchain applications without any hassle. Project Brainwave for deep learning acceleration Microsoft released a public preview of the highly anticipated Project Brainwave - a deep neural network processing solution designed to make Azure the fastest cloud to run deep learning and other AI-based solutions. Per Nadella, the CEO of Microsoft who made this announcement, Brainwave will equip the developers with the necessary processing power to deploy machine learning and deep learning models with a higher performance potential, much beyond what they can expect from a CPU or GPU. Also, this project is expected to lead to five times lower hardware latency than Google’s TPU (Tensor Processing Unit). Is Brainwave Microsoft’s answer to Google’s TPU? Check out our detailed comparison on the two chips. Other important announcements on Day 1 Apart from these significant enhancements for Azure, Microsoft also announced a whole host of features to improve their other existing offerings, including Microsoft 365, Sharepoint, Excel, and Microsoft Bot Framework, among others. Here are the major announcements in this regard: Integration of Amazon’s Alexa and Microsoft’s Cortana for Windows devices Windows Machine Learning, a new AI platform for developers to build machine learning models on the cloud was announced Updated Microsoft Bot Framework was announced, with richer voice customization Integration of Azure Search with Cognitive Services was announced, for quicker searches powered by Artificial Intelligence Azure Kubernetes services will be integrated with the Azure IoT Edge for better container orchestration Microsoft Excel will now support visualizations designed in Microsoft Power BI Microsoft 365 will make it easier to customize and publish business applications, with the help of the Microsoft Teams API In the midst of a major 3-way power struggle between Amazon, Google and Microsoft, these announcements made by Microsoft in the Build 2018 conference feel like a breath of fresh air, especially for the Microsoft developers. Their vision of transforming Microsoft’s cloud platform and other services into an intelligent cloud powered by Artificial Intelligence and other trending technologies seems to be well underway. It will be interesting to see what Google’s response will be in their Google I/O conference which will be underway tonight, and not to mention Amazon re:Invent 2018 which takes place later in the year. Here are the highlights of day 1 of Microsoft Build in under 15 minutes, if you’re interested. Serverless computing wars: AWS Lambdas vs Azure Functions Introducing Azure Sphere – A secure way of running your Internet of Things devices How to get started with Azure Stream Analytics and 7 reasons to choose it  

Last week, Bleeping Computer reported that the latest versions of Google Chrome, Safari, Opera, and Microsoft Edge will not allow users to disable hyperlink auditing that was possible in previous versions. What is hyperlink auditing? The Web Applications 1.0 specification introduced a new feature in HTML5 called hyperlink auditing for tracking clicks on the links. To track user clicks, the “a” and “area” elements support a “ping” attribute that takes one or more URIs as a value. For example: When you click on the hyperlink, the “href” link will be loaded as expected, but additionally, the browser will also send an HTTP POST request to the ping URL. The request headers can then be examined by the scripts that receive the ping POST request to find out where the ping came from. Which browsers have made hyperlink auditing compulsory? After finding this issue in Safari Technology Preview 72, Jeff Johnson, a professional Mac, and iOS software engineer reported this to Apple. Despite this, Apple released Safari 12.1 without any settings to disable hyperlink auditing. Prior to Safari 12.1, users were able to disable this feature with a hidden preference. Similar to Safari, in Google Chrome hyperlink auditing was enabled by default. Users could previously disable this by going to “chrome://flags#disable-hyperlink-auditing” and setting the flag to “Disabled”. But, in Chrome 74 Beta and Chrome 75 Canary builds, this flag has been completely removed. Microsoft Edge and Opera 61 Developer build also removes the option to disable/enable hyperlink auditing. Firefox and Brave, on the other hand, have disabled hyperlink auditing by default. In Firefox 66, Firefox Beta 67, and Firefox Nightly 68 users can enable it using the browser.send_pings setting, the Brave browser, however, does not allow users to enable it at all. How people are reacting to this development? The hyperlink auditing feature has received mixed reactions from developers and users. While some were concerned about its privacy implications, others think that this process makes the user experience more transparent. Sharing how this development can be misused, Chris Weber co-founder of Casaba Security wrote in a blog post,  “the URL could easily be appended with junk causing large HTTP requests to get sent to an inordinately large list of URIs. Information could be leaked in the usual sense of Referrer/Ping-From leaks.” One Reddit user said that this feature is privacy neutral as this kind of tracking can be done with JavaScript or non-JavaScript redirects. Sharing other advantages of the ping attribute, another user said, “The ping attribute for hyperlinks aims to make this process more transparent, with additional benefits such as optimizing network traffic to the target page loads more quickly, as well as an option to disable sending the pings for more user-friendly privacy.” Though this feature brings some advantages, the Web Hypertext Application Technology Working Group (WHATWG) encourages user agents to put control in the hands of the users by providing them a feature to disable this behavior. “User agents should allow the user to adjust this behavior, for example in conjunction with a setting that disables the sending of HTTP `Referer` (sic) headers. Based on the user's preferences, UAs may either ignore the ping attribute altogether or selectively ignore URLs in the list,” mentions WHATWG. To read the full story, visit Bleeping Computer. Google dissolves its Advanced Technology External Advisory Council in a week after repeat criticism on selection of members Microsoft’s #MeToo reckoning: female employees speak out against workplace harassment and discrimination Mozilla is exploring ways to reduce notification permission prompt spam in Firefox

Apache Releases Trafodion, SAP announces general availability of SAP Predictive Analytics application edition, Pachyderm 1.7, and more in today’s top stories and news around data science, machine learning, and deep learning. Top Data Science news of the Day The 5 biggest announcements from TensorFlow Dev Summit 2018 Other Data Science News at a Glance Apache Releases Trafodion, a webscale SQL-on-Hadoop solution. Apache Trafodion has moved from incubator status to become a high level project. Trafodion enables transactional or operational workloads on Apache Hadoop. Read more on I Programmer SAP has announced general availability of the application edition of SAP Predictive Analytics software, to help enterprise clients harness machine learning. With this, one can create and manage predictive models that deliver powerful data-driven insights to every business user across the enterprise in real-time. Read more on inside SAP IBM’s GPU-Accelerated Semantic Similarity Search at Scale Shows ~30000x Speed Up. The proposed model is a linear-complexity RWMD that avoids wasteful and repetitive computations and reduces the average time complexity to linear. Read more on IBM Research Blog Announcing Pachyderm 1.7, an open source and enterprise data science platform that is enabling reproducible data processing at scale. Read more on Medium Mobodexter announces general availability of Paasmer 2.0, a dockerized version of their IoT Edge software that removes the hardware dependency to run Paasmer Edge Software. Paasmer becomes one of the few IoT software platforms in the world to add the Docker capability on the IoT Edge. Read more on Benzinga Announcing AIRI: Integrated AI-Ready Infrastructure for Deploying Deep Learning at Scale. AIRI is purpose-built to enable data architects, scientists and business leaders to extend the power of the NVIDIA DGX-1 and operationalise AI-at-scale for every enterprise. Read more on Scientific Computing World

There are murmurs on the internet that tools like Puppet are being killed off by Kubernetes. The reality is a little more complex. True, Kubernetes poses some challenges to various players in the infrastructure automation market, but they nevertheless remain important tools for engineers charged with managing infrastructure. Kubernetes is forcing this market to adapt - and with Puppet announcing new tools and features to its portfolio in Puppet Enterprise 2019.1 yesterday, this it's clear that the team are making the necessary strides to remain a key part of the infrastructure automation landscape. Update: This article was amended to highlight that Puppet Enterprise is a distinct product separate from Continuous Delivery for Puppet Enterprise. What's new for Puppet Enterprise 2019.1? There are two key elements to the Puppet announcement: enhanced integration with Puppet Bolt - an open source, agentless task runner - and improved capabilities with Continuous Delivery for Puppet Enterprise. Puppet Bolt Puppet Bolt, the Puppet team argue, offers a really simple way to get started with infrastructure automation "without requiring an agent installed on a remote target." The Puppet team explain that Puppet Bolt essentially allows users to expand the scope of what they can automate without losing the consistency and control that you'd expect when using a tool like Puppet. This has some significant benefits in the context of Kubernetes. Bryan Belanger, Principal Consultant at Autostructure, said "We love using Puppet Bolt because it leverages our existing Puppet roles and classifications allowing us to easily make changes to large groups of servers and upgrade Kubernetes clusters quicker, which is often a pain if done manually." Belanger continues, saying "with the help of Puppet Bolt, we were also able to fix more than 1,000 servers within five minutes and upgrade our Kubernetes clusters within four hours, which included coding and tasks." Continuous Delivery for Puppet Enterprise Updates to the Continuous Delivery product aim to make DevOps practices easier - the Puppet team are clearly trying to make it easier for organizations to empower their colleagues and continue to build a culture where engineers are not simply encouraged to be responsible for code deployment, but also able to do it with minimal fuss. Module Delivery Pipelines now mean modules can be independently deployed without blocking others, while Simplified Puppet Deployments aims to make it easier for engineers that aren't familiar with Puppet to "push simple infrastructure changes immediately and easily perform complex rolling deployments to a group of nodes in batches in one step." But there is also another dimension that aims to help engineers take pro-active steps to tackle resiliency and security issues. With Impact Analysis teams will be able to look at the potential impact of a deployment before it's done. Read next: “This is John. He literally wrote the book on Puppet” – An Interview with John Arundel What's the big idea behind this announcement? The over-arching narrative that's coming from the top is about supporting teams to scale their DevOps processes. It's about making organizations' 'automation footprint' more manageable. "IT teams need a simple way to get started with automation and a solution that grows with them as their automation footprint grows," Matt Waxman, Head of Product at Puppet, explains. "You shouldn’t have to throw away your existing scripts or tools to scale automation across your organization. Organizations need a solution that is extensible — one that complements their current automation efforts and helps them scale beyond individuals to multiple teams." Puppet Enterprise 2019.1 will be out on general availability on May 7 2019. Learn more here.

Apple announced that it has finished acquiring Shazam, a widely popular and highly rated music app, earlier this week. Shazam is a music discovery app which currently has more than 100 million monthly active users and has been downloaded over 1 billion times around the world. It allows users to discover and identify songs with just a few clicks. “Apple and Shazam have a long history together. Shazam was one of the first apps available when we launched the App Store and it has become a favorite app for music fans everywhere,” mentioned Oliver Schusser, Vice President, Apple Music, in the press release. The price of this acquisition hasn’t been specified anywhere, but as per Recode, it is estimated to be around $400 million. The news of this acquisition comes three weeks after the EU regulators gave a go-ahead signal to Apple. When Apple mentioned about its plans to buy Shazam for $400 million back in December 2017, EU regulators started an investigation into this acquisition. This was over the concern that Apple’s acquisition of Shazam would potentially give Apple an unfair advantage over its rivals such as Spotify. “At this stage, the Commission is concerned that, following the takeover of Shazam, Apple would obtain access to commercially sensitive data about customers of its competitors. Access to such data could allow Apple to directly target its competitors' customers and encourage them to switch to Apple Music. As a result, the competing music streaming services could be put at a competitive disadvantage”, reads the EU  press release. Users all around the world identify songs using the Shazam app over 20 million times every day. Additionally, it helps people share video, audio or printed content across different devices and mediums. It also helps music fans follow their favorite artists. Whether Apple has plans of integrating the Shazam app with Apple music or not requires another official announcement. For now, Apple aims to make Shazam ad-free. This will ensure that users are able to enjoy music, without any form of interruption. “With a shared love of music and innovation, we are thrilled to bring our teams together to provide users even more great ways to discover, experience and enjoy music”, mentions Schusser. For more information, check out Apple’s official announcement. Apple stocks soar just shy of $1 Trillion market cap as revenue hits $53.3 Billion in Q3 earnings 2018 Apple releases iOS 12 beta 2 with screen time and battery usage updates among others Apple announces a Special Event to reportedly launch new products including “iPhone XS” and OS updates

Day 2 of the Amazon AWS re:Invent 2018 conference kicked off with just as much enthusiasm with which it began. With some more announcements and releases scheduled for the day, the conference is proving to be a real treat for AWS Developers. Amongst announcements like Amazon Comprehend Medical, New container products in the AWS marketplace; Amazon also announced Amazon DynamoDB Transactions and Amazon CloudWatch Logs Insights. We will also take a look at Amazon re:Inforce 2019 which is a new conference solely to be launched for cloud security. Amazon DynamoDB Transactions Customers have used Amazon DynamoDB for multiple use cases, from building microservices and mobile backends to implementing gaming and Internet of Things (IoT) solutions. Amazon DynamoDB is a non-relational database delivering reliable performance at any scale. It offers built-in security, backup and restore, and in-memory caching along with being a fully managed, multi-region, multi-master database that provides consistent single-digit millisecond latency. DynamoDB with native support for transactions will now help developers to easily implement business logic that requires multiple, all-or-nothing operations across one or more tables. With the help of DynamoDB transactions, users can take advantage of the atomicity, consistency, isolation, and durability (ACID) properties across one or more tables within a single AWS account and region. It is the only non-relational database that supports transactions across multiple partitions and tables. Two new DynamoDB operations have been introduced for handling transactions: TransactWriteItems, a batch operation that contains a write set, with one or more PutItem, UpdateItem, and DeleteItem operations. It can optionally check for prerequisite conditions that need to be satisfied before making updates. TransactGetItems, a batch operation that contains a read set, with one or more GetItem operations. If this request is issued on an item that is part of an active write transaction, the read transaction is canceled. Amazon CloudWatch Logs Insights Many AWS services create logs. Data points, patterns, trends, and insights embedded within these logs can be used to understand how an applications and a users AWS resources are behaving, identify room for improvement, and to address operational issues. However, the raw logs have a huge size, making analysis difficult. Considering individual AWS customers routinely generate 100 terabytes or more of log files each day, the operations become complex and time-consuming. Enter CloudWatch Logs Insights designed to work at cloud scale, without any setup or maintenance required. It goes through massive logs in seconds and provides a user with fast, interactive queries and visualizations. CloudWatch Logs Insights includes a sophisticated ad-hoc query language, with commands to perform complicated operations efficiently. It is a fully managed service and can handle any log format, and auto-discovers fields from JSON logs. What's more? Users can also visualize query results using line and stacked area charts, and add queries to a CloudWatch Dashboard. AWS re:Inforce 2019 In addition to these releases, Amazon also announced that AWS is launching a conference dedicated to cloud security called ‘AWS re:Inforce’, for the very first time. The inaugural AWS re:Inforce, a hands-on gathering of like-minded security professionals, will take place in Boston, MA on June 25th and 26th, 2019 at the Boston Exhibit and Conference Center. Here is what the AWS re:Inforce 2019 conference is expected to cover: Deep dive into the latest approaches to security best practices and risk management utilizing AWS services, features, and tools. Direct access to customers to the latest security research and trends from subject matter experts, along with the opportunity to participate in hands-on exercises with our services. There are multiple learning tracks to be covered over this 2-day conference including a technical track and business enablement track, designed to meet the needs of security and compliance professionals, from C-suite executives to security engineers, developers, risk and compliance officers, and more. The conference will also feature sessions on Identity & Access Management, Infrastructure Security, Detective Controls, Governance, Risk & Compliance, Data Protection & Privacy, Configuration & Vulnerability Management, and much more. Head over to What’s new with AWS to stay updated on upcoming AWS announcements. Day 1 at the Amazon re: Invent conference – AWS RoboMaker, Fully Managed SFTP Service for Amazon S3, and much more! Amazon introduces Firecracker: Lightweight Virtualization for Running Multi-Tenant Container Workloads AWS introduces ‘AWS DataSync’ for automated, simplified, and accelerated data transfer

Cirq is a Python library for writing quantum circuits and running them against quantum computers created by Google. Cirq 0.4.0 is now released and is available on GitHub. Changes in Cirq 0.4.0 themes The API is now more pythonic and more consistent with respect to breaking changes and refactoring. The simulation is faster. New functionality in Cirq 0.4.0 The following functions, parameters are added. cirq.Rx, cirq.Ry, and cirq.Rz cirq.XX, cirq.YY, cirq.ZZ, and cirq.MS related to the Mølmer–Sørensen gate cirq.Simulator cirq.SupportsApplyUnitary protocol is added to specify fast simulation methods cirq.Circuit.reachable_frontier_from and cirq.Circuit.findall_operations_between cirq.decompose sorted(qubits) and cirq.QubitOrder.DEFAULT.order_for(qubits) are now equivalent cirq.experiments.generate_supremacy_circuit_[...] dtype parameters are added to control the precision versus speed of simulations cirq.TrialResult helper methods (dirac_notation / bloch_vector / density_matrix) cirq.TOFFOLI and cirq.CCZ can be raised to powers Breaking changes in Cirq 0.4.0 Most of the gate classes have been standardized. They can now take an exponent argument and have a name which is of the form NamePowGate. For example, RotXGate is now XPowGate and it no longer takes rads, degs, or half_turns. The xmon gate set has now been merged into the common gate set. The capability marker classes have been replaced by magic method protocols. As an example, gates now just implement a _unitary_ method as opposed to inheriting from KnownMatrix. cirq.Extensions and cirq.PotentialImplementation are removed. Many decomposition classes and methods have been moved from cirq.google.* to cirq.*. Example: cirq.google.EjectFullW is now cirq.EjectPhasedPaulis. The classes and methods related to line placement are moved into cirq.google. Notable bug fixes A two-qubit gate decomposition will no longer produce a glut of single qubit gates. When multi-line entries are given, circuit diagrams stay aligned. They now include "same moment" indicators. The false-positives and false-negatives are fixed in cirq.testing.assert_circuits_with_terminal_measurements_are_equivalent. Many repr methods returning code are fixed that assumed from cirq import * instead of import cirq. Example code now runs in both Python 2 and Python 3 without the need for transpilation. Notable dev changes The test files now import cirq instead of just specific modules. There is better testing and packaging of scripts. The package versions for Python 2 and Python 3 are no longer different. cirq.value_equality decorator is added. New cirq.testing methods and classes are added. Additions to contrib cirq.contrib.acquaintance: New utilities for defining permutation gates cirq.contrib.paulistring: Utilities for optimizing non-Clifford operations which are separated by Clifford operations cirq.contrib.tpu: Utilities for converting circuits into an executable form to be used on cloud TPUs. This requires TensorFlow. Google AdaNet, a TensorFlow-based AutoML framework Graph Nets – DeepMind’s library for graph networks in Tensorflow and Sonnet A new Model optimization Toolkit for TensorFlow can make models 3x faster

This Tuesday, Microsoft announced .NET Core 3 Preview 2 with new features in .NET Core 3 and C# 8. C# 8 The eighth iteration of C# is a major release and includes many new features. Declarations Statements don’t need to be indented now. Switch expressions C# 8 comes with switch expressions in which you can use the new syntax. Terser syntax returns a value as it is an expression. It’s fully integrated with pattern matching. Async streams The compiler and framework libraries should match correctly for async streams to work. You will need .NET Core 3.0 Preview 2 and Visual Studio 2019 Preview 2. Alternatively, you can also use the C# extension for Visual Studio Code. Floating point improvements in IEEE The goal is to expose all operations that are needed and they are behaviorally compliant with the IEEE spec. A fast in-box JSON Writer & JSON document Two new objects were added—System.Text.Json.Utf8JsonWriter and System.Text.Json.JsonDocument. Utf8JsonWriter The Utf8JsonWriter enables a high-performance, non-cached way to write UTF-8 encoded JSON text from common .NET types. JsonDocument System.Text.Json.JsonDocument is also added built on top of the Utf8JsonReader. JsonDocument provides enables parsing JSON data and builds a read-only Document Object Model (DOM). It can be queried to support enumeration and random access. Assembly Unloadability Assembly unloadability is a new ability of AssemblyLoaderContext. It is transparent and exposed with only a few new APIs. A loader context to be unloaded with this. This releases all of the memory for static fields, instantiated types, and the assembly itself. Visual Studio support Using .NET Core 3 for development requires using Visual Studio 2019. WPF and Windows Forms templates were added to the New Project Dialog for easier access via the command line. These were a select few updates from the new .NET Core 3 Preview 2, for a complete list of changes, visit the Microsoft Blog. Microsoft Connect(); 2018: .NET foundation open membership, .NET Core 2.2, .NET Core 3 Preview 1 released, WPF, WinUI, Windows forms open sourced What to expect in ASP.NET Core 3.0 .NET Core 3.0 and .NET Framework 4.8 more details announced

Following on from the popularity of the Python bundle at the start of January, Packt is once again working with Humble Bundle to bring readers a selection of tech resources - this time on all things mobile development. Find the offer on Humble Bundle. Featuring a combination of Packt’s most popular and latest, cutting-edge mobile development titles, such as Mastering iOS 11 Programming, Second Edition, and Mastering React Native, it’s an opportunity for mobile developers - from beginners to experienced professionals - to stock up on skills for 2018. ‘Mobile development is a field where innovation is happening at an impressive rate - this means developers have a great opportunity to get involved in some really exciting projects’ says Heather Gopsill, Head of Channels at Packt. ‘The books we’ve put together with the team at Humble Bundle will help readers develop essential skills to equip them for the future of mobile. That they can do this while donating to incredible causes is even better!’ Readers can pay from $1 to purchase: Android Application Development Cookbook, Second Edition iOS 10 Programming for Beginners Learning Ionic, Second Edition Creating Cross Platform Games with Xamarin Three months of Mapt Pro Readers who pay from $8 can also purchase: Android Programming for Beginners Mastering Android Studio 3 Swift 4 Protocol-oriented Programming Xamarin 4.x Cross Platform Application Development Mastering React Native Ionic 2 Solutions Kotlin Fundamentals React Native Projects And readers who contribute from $15 can get all of those titles as well as these: React Native Cookbook Android Development with Kotlin Mastering Cross-Platform Development with Xamarin Mastering iOS 11 Programming, Second Edition Mastering Swift 4, Fourth Edition React and React Native Swift 4 Programming Cookbook Developing iOS 11 Applications Using Swift 4 iOS 11 Programming with Swift Mastering Kotlin for Android Development Customers will be invited to donate to featured charities code.org and Charity: Water, but will also be able to select from Humble Bundle’s huge database of partner charities. The bundle offer ends on 12th February 2018.

It has been a tough few months for some of the U.S.' biggest tech companies. Political upheaval has placed a big focus on data, privacy, and government contracts not only in the tech industry but across the public too. You could easily argue that these organizations have been quiet in spite of considerable noise, but that might be changing. Brad Smith, Microsoft President and Chief Legal Officer today (13 July) wrote a blog post arguing in favor of regulation of facial recognition technology. What Brad Smith argues in his blog post In his blog post Brad Smith sets the context clearly. He argues that while facial recognition technology can be "both positive and potentially even profound," it also "raises a critical question: what role do we want this type of technology to play in everyday society?" For Smith, that question can't be answered by tech companies alone. "As a general principle," he writes, "it seems more sensible to ask an elected government to regulate companies than to ask unelected companies to regulate such a government." As Smith also notes, we shouldn't actually be that surprised at a company asking for government regulation. In other industries, it's actually common. Smith cites the aviation, food and pharmaceutical industries as areas in which corporations work closely with government to develop regulation and legislation. However, Smith doesn't outline anything specific with regards to legislation. Instead he is much more keen to urge a "thoughtful approach" from government, as a challenge to ways of using facial recognition technology that could be exploitative. He does, however, argue for Congress to form a bipartisan expert commission to properly assess the uses (and abuses) of facial recognition technology. "The purpose of such a commission should include advice to Congress on what types of new laws and regulations are needed, as well as stronger practices to ensure proper congressional oversight of this technology across the executive branch," he explains. Does Brad Smith think tech companies still have responsibility? In short, yes. Although Smith believes the debate and discussion around facial technology has to take place in a civic space away from the demands of industry and government, he is forthright in asserting technology companies' responsibility in developing and deploying new technologies. He outlines 4 things that the tech industry can do to ensure that facial recognition technology is used ethically: Working to minimize bias in machine learning and artificial intelligence systems More transparency in how facial recognition technology is being developed and used Being more cautious in how facial recognition technology is applied Actively participating in public policy discussions around facial recognition technology Are things changing in tech? Although it's only a blog post, this is one of the first instances of a senior figure at a tech company talking positively about working with government. Contrasted with Mark Zuckerberg's Congressional testimony, it couldn't look more different. At a time when conversation around the ethics of technology has never felt more visible and urgent, Brad Smith's intervention is welcome. How the wider tech world and government responds is another matter. Read next: Microsoft condemns ICE activity at U.S. border but still faces public and internal criticism Tech’s culture war: entrepreneur egos v. engineer solidarity Amazon is selling facial recognition technology to police

Today, FaunaDB, announced the general availability of FaunaDB managed serverless database service. The new service will provide Fauna’s small and medium-sized enterprises (SMEs) and partners with flexibility and a customer-dedicated deployment of FaunaDB.  In a statement, Evan Weaver, CEO of Fauna said, “We are breaking new ground in the industry by offering the first fully managed serverless service, and we now deliver the best of both worlds.” He further adds, “Developers wanting a powerful data management component for cutting-edge app development can use FaunaDB, while companies wanting to avoid hands-on cloud configuration and maintenance can choose our managed serverless offering.” FaunaDB managed serverless is a mature data management solution which will include all the features of FaunaDB. It currently supports Amazon Web Services (AWS) and Google Cloud Platform (GCP), and will come up with support for Azure soon. Its capacity is termed and priced on a monthly or annual basis. The serverless database is assisted by Fauna customer success enterprise support, which will give users access to technical support and customer service. Operational controls delivered by FaunaDB Managed Serverless  Enterprise-grade support and SLAs Change data feed or stream Query log auditing Operational monitoring integration Customer-defined local endpoints Customer-defined data locality Backup and restore tailored to meet compliance needs Isolated environments as needed for development, testing and staging Nextdoor, a private social network, is already using FaunaDB Managed Serverless Database Service. The co-founder and chief architect of Nextdoor, Prakash Janakiraman says, “We selected FaunaDB for its API flexibility and scalability, security and availability to support global use of our mobile app. We are now using the managed service for its flexible configuration options and capabilities such as multiple development environments, change data feed and query log auditing.” Fauna announces Jepsen results for FaunaDB 2.5.4 and 2.6.0 GraphQL API is now generally available After PostgreSQL, DigitalOcean now adds MySQL and Redis to its managed databases’ offering