Cutting Through the Mire of Tablet Issue Production

first_imgEach publisher has approached tablets at its own pace, with its own purpose. The result has left a scattered set of protocols across the industry.The International Digital Enterprise Alliance (IDEAlliance), an association serving players across the digital media supply chain, is attempting to simplify the process of tablet issue production by eliminating many of the competing formats and workflows. The goal is an industry standard called OpenEFT—guidelines to direct the packaging, delivery and display of digital magazines for everyone in the ecosystem. OpenEFT’s final draft was unveiled late last month.“We, as publishers, would like to be able to provide a designed-for-tablet, interactive edition to all the newsstands,” says Sean Keefe, executive director of publishing technology for Hearst Magazines. “But right now, not all of them take the same file formats.”The benefits for publishers are two-fold. Tablet issue production would become a more efficient process, while the barriers to third-party innovation would be lowered. Tablet issue production can be convoluted now. Hearst currently produces up to three formats (and several variants) of its magazines, depending on the brand and the newsstand they’re working with; Next Issue Media, a digital newsstand, is forced to adapt about six formats for its storefront. Many of those conversions are labor intensive and require quality assurance testing at multiple points.Ideally, says Keith Barraclough, CTO and vice president of products for Next Issue, the exchange of files would be simplified, QA would only be needed once and the process could be automated.“Whether OpenEFT can do all this as it goes through its standardization process and tools and manufacturers come along and adopt, that’s all a big ‘TBD,’” he says. “But that’s the nirvana we’re looking for.”An open specification already exists, called ePub, but it was built to handle books, not magazines.“The orientation toward imagery, layout and the subtlety of the navigation of a magazine is something that’s evolved more,” Barraclough says.While Dianne Kennedy, vice president of emerging technologies for IDEAlliance, says OpenEFT is closely modeled after ePub, she adds that the need for tablet-optimized ad units is another major reason the book-centric format needed to be tweaked for digital magazines.Magazine staff have to manipulate the units from the agency, often without being exactly sure of how the final product was supposed to render. The costs and confusion make their use rare.“Magazines, unlike books, rely a lot on the ad model,” Kennedy says. “There is no specification for the exchange and rendering of this interactive content, so the magazines have been limiting the number of interactive ads they will accept.”Regardless of how or why they started with tablet editions, publishers will agree that improving production efficiency is beneficial.Now, it’s up to them to adopt the standard.last_img read more

PHOTOS Wilmingtons Boy Scout Troop 136 Holds Car Wash Fundraiser For McLaren Family

first_imgLike Wilmington Apple on Facebook. Follow Wilmington Apple on Twitter. Follow Wilmington Apple on Instagram. Subscribe to Wilmington Apple’s daily email newsletter HERE. Got a comment, question, photo, press release, or news tip? Email wilmingtonapple@gmail.com.Share this:TwitterFacebookLike this:Like Loading… RelatedWilmington Boy Scouts Troop 136 To Hold Car Wash On September 8 To Benefit McLaren Family Following TragedyIn “Community”Cub Scout Pack 136 Announce Pumpkin Sale, Haunted Trail Walk & Haunted House FundraisersIn “Community”Wilmington Boy Scouts To Hold Car Wash On May 19In “Community” WILMINGTON, MA — Wilmington’s Boy Scout Troop 136 held a Car Wash fundraiser on Saturday, September at the Friendship Lodge.All proceeds benefited the McLaren family of Wilmington. On July 30, Tom McLaren was injured in a motorcycle accident on his way to work on Route 128. He remains hospitalized with serious injuries. Tom’s family includes his wife Wanda, and his two children, Leila and David. David is a member of Troop 136.For those who were out of town and unable to attend, a GoFundMe was set up by friends of the family at http://www.gofundme.com/support-for-the-mclaren-family. Any and all donations are greatly appreciated and will go directly to the family for living and medical expenses.Below are photos of the event, from Dick Searfoss, posted on the Friendship Lodge’s website:last_img read more

Conditions for Egypts Morsi could lead to premature death Report

first_imgEgyptian president Mohamed MorsiDeposed Egyptian president Mohamed Morsi is being detained in conditions that fail to meet international standards and could lead to his premature death, according to a report released Wednesday by three British lawmakers.Morsi, who has a history of ill-health including diabetes, liver and kidney disease, is not receiving the adequate medical care required, the members of parliament found.The parliamentarians — who formed an Independent Detention Review Panel — also highlighted that 66-year-old Morsi is kept in solitary confinement for 23 hours a day, with just one hour for him to exercise alone.That could be classified as torture by the UN special rapporteur on torture and other cruel, inhuman or degrading treatment or punishment, the panel noted.”Our conclusions are stark,” said panel chair Crispin Blunt MP, presenting the findings in London. “On his health, the denial of basic medical treatment to which he is entitled could lead to his premature death.”The whole overseeing chain of command up to the current president would have responsibility for this.”The panel requested to visit Morsi in prison to review detention and health conditions, but said it received no response from Egyptian authorities.The report was compiled using “all available testimonies”, including witness statements, reports by NGOs and evidence submitted independently, it added.Abdullah Morsi, Morsi’s son, who told the panel he has been denied access to the deposed president along with other relatives and his legal team, was quoted as saying in the statement that their “fears and concerns have been confirmed by the findings”.He called on the international community to condemn his father’s treatment and “push the Egyptian government to allow his family to visit, and for him to receive medical care”.”We do not want him to die in prison,” he added.Morsi was Egypt’s first democratically elected civilian president following the 2011 overthrow of longtime leader Hosni Mubarak during the Arab Spring uprisings.But his year in power proved deeply divisive and he was ousted by current president Abdel Fattah al-Sisi, then the army chief, amid mass protests in 2013.last_img read more

Stranger Things Star Noah Schnapp Joins Neil Gaiman VR Adaptation Wolves in

first_img Popular on Variety Noah Schnapp of “Stranger Things” fame has joined the voice cast of “Wolves in the Walls,” an animated VR series based on Neil Gaiman’s children’s book by the same title. Schnapp will be voicing the brother of Lucy, the main character of “Wolves,” in the second chapter of the series, which is scheduled to premiere in April. “We believe that Noah Schnapp brings a special quality to the brother role,” said “Wolves” director Pete Billington. “As soon as he read his first line, we were smitten. We love him in ‘Stranger Things’ and can’t wait for audiences to hear his performance in ‘Wolves in the Walls.’” Fable, the immersive entertainment company behind “Wolves in the Walls,” shared the casting news exclusively with Variety ahead of Sundance. The company is also using the film festival to announce a new focus on what it calls virtual beings — characters that are powered by artificial intelligence and can respond to and interact with their audience. CREDIT: Courtesy of Fable ×Actors Reveal Their Favorite Disney PrincessesSeveral actors, like Daisy Ridley, Awkwafina, Jeff Goldblum and Gina Rodriguez, reveal their favorite Disney princesses. Rapunzel, Mulan, Ariel,Tiana, Sleeping Beauty and Jasmine all got some love from the Disney stars.More VideosVolume 0%Press shift question mark to access a list of keyboard shortcutsKeyboard Shortcutsplay/pauseincrease volumedecrease volumeseek forwardsseek backwardstoggle captionstoggle fullscreenmute/unmuteseek to %SPACE↑↓→←cfm0-9Next UpJennifer Lopez Shares How She Became a Mogul04:350.5x1x1.25×1.5x2xLive00:0002:1502:15center_img Fable plans to premiere “Whispers in the Night” this coming summer, when the company is also going to hold a virtual beings conference in San Francisco. But even with that new focus on virtual beings, Fable plans to continue to work on “Wolves in the Walls,” which the company wants to release to consumers once it has finished all 3 parts, likely in 2020.This week, Saatchi, Billington and Shamash argued that virtual beings powered by artificial intelligence can ultimately make such VR stories more meaningful, even if they may exist on multiple screens. Most consumers would not watch VR movies for longer than a couple of minutes, said Saatchi.However, smart displays and phones might provide an opportunity to interact with virtual characters far more often, and for longer periods of time — which could ultimately lead to characters inviting viewers to join them in VR again. “I don’t think it cannibalizes VR at all,” he said.And some of that artificial intelligence-based interactivity may even find its way back into “Wolves in the Walls,” suggested Shamash: “‘Wolves’ will be this living, breathing thing.” CREDIT: Courtesy of Fable “We are changing the make-up of our team radically to add machine learning folks,” said Fable co-founder and executive producer Edward Saatchi.Fable’s first foray into this new area of interactive story-telling with virtual beings is called “Whispers in the Night,” which is a kind of spin-off of “Wolves in the Walls.” In the piece, viewers get to interact with Lucy, the main character of “Wolves in the Walls,” and even have conversations with her. “‘Whispers is a natural language processing project where you can talk to a character,” said Saatchi.Much like “Wolves in the Walls,” “Whispers in the Night” is also a VR experience, but Saatchi said that the company was working on quickly bringing the character to other mediums as well, including smart displays like Facebook’s Portal and Amazon’s Echo Show.Fable wants to tie those different types of screens together by making Lucy a character that is not only able to respond to her audience, but actually remember things. “With ‘Whispers,’ we are exploring this idea of memory,” said the piece’s creative director Jessica Shamash. “She doesn’t reset and forget everything,” added Billington. And by remembering things that people tell her, Lucy is going to personalize the experience for each and every viewer.last_img read more

Will fund projects via longterm debt not fare hikes or tax payer

first_img“Loan is way forward (infrastructure) development. Countries like US, China and Europe have taken loans for development of their infrastructure,” Prabhu said in an interview to Lok Sabha TV.Asked whether the government is going in for privatisation of railways in future, he explained: “We are taking debt for development of railways infrastructure, that means we are not doing privatisation. Besides there will be no burden of development on passenger fare as well as tax payers money.” Also Read – I-T issues 17-point checklist to trace unaccounted DeMO cashPrabhu expressed confidence that institutions like LIC (in India),pension funds and sovereign funds can provide debt and they will not insist on early repayment of loan. “The LIC, pension fund and sovereign wealth funds don’t insist on repayment of loans in short term, rather they want us to pay in over 30 years,” he added.On hitting the ground running, he quoted a famous saying, “Rome was not built in a day. There are few things which would be done this year like 3000 unmanned crossings will be removed and work will start immediately to improve cleanliness, safety, security and surveillance.” The Minister hinted that some initiative like train-sets, redesigning of coaches, doubling and tripling of rail lines, may take longer than expected to be implemented. On running of bullet trains in India, he said, “Our thrust would be on basic facilities first like sanitation, time bound arrival of trains which is going to be implemented in the stipulated time period. Those would be focus areas.” Also Read – Lanka launches ambitious tourism programme to woo Indian touristsOn private participation in railways, Prabhu said that there would be a system to regulate private sector players willing to invest in station development projects. On decentralisation of power to improve efficiency of railways, he said,”This will happen for the first time that more responsibility will be given to officers. It is not on Railway Minister or Railway Board which will do everything.” Earlier, in his Budget speech, Prabhu said: “We will monetise our assets rather than sell them”.  On Special Purpose Vehicles (SPV), he said, “We have created new SPVs with the oil ministry, coal ministry… those will deliver. Rather than one entity, there will be multiple entities delivering.”last_img read more

Why TensorFlow always tops machine learning and artificial intelligence tool surveys

first_imgTensorFlow is an open source machine learning framework for carrying out high-performance numerical computations. It provides excellent architecture support which allows easy deployment of computations across a variety of platforms ranging from desktops to clusters of servers, mobiles, and edge devices. Have you ever thought, why TensorFlow has become so popular in such a short span of time? What made TensorFlow so special, that we seeing a huge surge of developers and researchers opting for the TensorFlow framework? Interestingly, when it comes to artificial intelligence frameworks showdown, you will find TensorFlow emerging as a clear winner most of the time. The major credit goes to the soaring popularity and contributions across various forums such as GitHub, Stack Overflow, and Quora. The fact is, TensorFlow is being used in over 6000 open source repositories showing their roots in many real-world research and applications. How TensorFlow came to be The library was developed by a group of researchers and engineers from the Google Brain team within Google AI organization. They wanted a library that provides strong support for machine learning and deep learning and advanced numerical computations across different scientific domains. Since the time Google open sourced its machine learning framework in 2015, TensorFlow has grown in popularity with more than 1500 projects mentions on GitHub. The constant updates made to the TensorFlow ecosystem is the real cherry on the cake. This has ensured all the new challenges developers and researchers face are addressed, thus easing the complex computations and providing newer features, promises, and performance improvements with the support of high-level APIs. By open sourcing the library, the Google research team have received all the benefits from a huge set of contributors outside their existing core team. Their idea was to make TensorFlow popular by open sourcing it, thus making sure all new research ideas are implemented in TensorFlow first allowing Google to productize those ideas. Read Also: 6 reasons why Google open sourced TensorFlow What makes TensorFlow different from the rest? With more and more research and real-life use cases going mainstream, we can see a big trend among programmers, and developers flocking towards the tool called TensorFlow. The popularity for TensorFlow is quite evident, with big names adopting TensorFlow for carrying out artificial intelligence tasks. Many popular companies such as NVIDIA, Twitter, Snapchat, Uber and more are using TensorFlow for all their major operations and research areas. On one hand, someone can make a case that TensorFlow’s popularity is based on its origins/legacy. TensorFlow being developed under the house of “Google” enjoys the reputation of the household name. There’s no doubt, TensorFlow has been better marketed than some of its competitors. Source: The Data Incubator However that’s not the full story. There are many other compelling reasons why small scale to large scale companies prefer using TensorFlow over other machine learning tools TensorFlow key functionalities TensorFlow provides an accessible and readable syntax which is essential for making these programming resources easier to use. The complex syntax is the last thing developers need to know given machine learning’s advanced nature. TensorFlow provides excellent functionalities and services when compared to other popular deep learning frameworks. These high-level operations are essential for carrying out complex parallel computations and for building advanced neural network models. TensorFlow is a low-level library which provides more flexibility. Thus you can define your own functionalities or services for your models. This is a very important parameter for researchers because it allows them to change the model based on changing user requirements. TensorFlow provides more network control. Thus allowing developers and researchers to understand how operations are implemented across the network. They can always keep track of new changes done over time. Distributed training The trend of distributed deep learning began in 2017, when Facebook released a paper showing a set of methods to reduce the training time of a convolutional neural network model. The test was done on RESNET-50 model on ImageNet dataset which took one hour to train instead of two weeks. 256 GPUs spread over 32 servers were used. This revolutionary test has open the gates for many research work which have massively reduced the experimentation time by running many tasks in parallel on multiple GPUs. Google’s distributed TensorFlow has allowed all the researchers and developers to scale out complex distributed training using in-built methods and operations that optimizes distributed deep learning among servers. . Google’s distributed TensorFlow engine which is part of the regular TensorFlow repo, works exceptionally well with the existing TensorFlow’s operations and functionalities. It has allowed exploring two of the most important distributed methods: Distribute the training time of a neural network model over many servers to reduce the training time. Searching for good hyperparameters by running parallel experiments over multiple servers. Google has given distributed TensorFlow engine the required power to steal the share of the market acquired by other distributed projects such as Microsoft’s CNTK, AMPLab’s SparkNet, and CaffeOnSpark. Even though the competition is tough, Google has still managed to become more popular when compared to the other alternatives in the market. From research to production Google has, in some ways, democratized deep learning., The key reason is TensorFlow’s high-level APIs making deep learning accessible to everyone. TensorFlow provides pre-built functions and advanced operations to ease the task of building different neural network models. It provides the required infrastructure and hardware which makes them one of the leading libraries used extensively by researchers and students in the deep learning domain. In addition to research tools, TensorFlow extends the services by bringing the model in production using TensorFlow Serving. It is specifically designed for production environments, which provides a flexible, high-performance serving system for machine learning models. It provides all the functionalities and operations which makes it easy to deploy new algorithms and experiments as per changing requirements and preferences. It provides an excellent feature of out-of-the-box integration with TensorFlow models which can be easily extended to serve other types of models and data. TensorFlow’s API is a complete package which is easier to use and read, plus provides helpful operators, debugging and monitoring tools, and deployment features. This has led to growing use of TensorFlow library as a complete package within the ecosystem by the emerging body of students, researchers, developers, production engineers from various fields who are gravitating towards artificial intelligence. There is a TensorFlow for web, mobile, edge, embedded and more TensorFlow provides a range of services and modules within their existing ecosystem making them as one of the ground-breaking end-to-end tools to provide state-of-the-art deep learning. TensorFlow.js for machine learning on the web JavaScript library for training and deploying machine learning models in the browser. This library provides flexible and intuitive APIs to build and train new and pre-existing models from scratch right in the browser or under Node.js. TensorFlow Lite for mobile and embedded ML It is a TensorFlow lightweight solution used for mobile and embedded devices. It is fast since it enables on-device machine learning inference with low latency. It supports hardware acceleration with the Android Neural Networks API. The future releases of TensorFlow Lite will bring more built-in operators, performance improvements, and will support more models to simplify the developer’s experience of bringing machine learning services within mobile devices. TensorFlow Hub for reusable machine learning A library which is used extensively to reuse machine learning models. Thus you can transfer learning by reusing parts of machine learning models. TensorBoard for visual debugging While training a complex neural network model, the computations you use in TensorFlow can be very confusing. TensorBoard makes it very easy to understand and debug your TensorFlow programs in the form of visualizations. It allows you to easily inspect and understand your TensorFlow runs and graphs. Sonnet Sonnet is a DeepMind library which is built on top of TensorFlow extensively used to build complex neural network models. All of this factors have made the TensorFlow library immensely appealing for building a wide spectrum of machine learning and deep learning projects. This tool has become a preferred choice for everyone from space research giant NASA and other confidential government agencies, to an impressive roster of private sector giants. Road Ahead for TensorFlow TensorFlow no doubt is better marketed compared to the other deep learning frameworks. The community appears to be moving very fast. In any given hour, there are approximately 10 people around the world contributing or improving the TensorFlow project on GitHub. TensorFlow dominates the field with the largest active community. It will be interesting to see what new advances TensorFlow and other utilities make possible for the future of our digital world. Continuing the recent trend of rapid updates, the TensorFlow team is making sure they address all the current and active challenges faced by the contributors and the developers while building machine learning and deep learning models. TensorFlow 2.0 will be a major update, we can expect the release candidate by next year early March. The preview version of this major milestone is expected to hit later this year. The major focus will be on ease of use, additional support for more platforms and languages, and eager execution will be the central feature of TensorFlow 2.0. This breakthrough version will add more functionalities and operations to handle current research areas such as reinforcement learning, GANs, building advanced neural network models more efficiently. Google will continue to invest and upgrade their existing TensorFlow ecosystem. According to Google’s CEO, Sundar Pichai “artificial intelligence is more important than electricity or fire.” TensorFlow is the solution they have come up with to bring artificial intelligence into reality and provide a stepping stone to revolutionize humankind. Read more The 5 biggest announcements from TensorFlow Developer Summit 2018 The Deep Learning Framework Showdown: TensorFlow vs CNTK Tensor Processing Unit (TPU) 3.0: Google’s answer to cloud-ready Artificial Intelligencelast_img read more