Java Developers Can Dish Out Tastier Web Apps with JSweet

Java developers get a sweet treat this Christmas by the launch of the JSweet via open source. JSweet will the java developers in utilizing their Java skills for building much better and highly interactive and rich Web Apps with JSweet. This particular technology ‘transpiles’ from Java programming language to TypeScript and finally into JavaScript. TypeScript is essentially a Microsoft technology, which compiles programming codes into JavaScript. JSweet has been developed by a Paris based software engineering company, Chincheo, which aimed at making the life of Java bit fun and easier in building Web apps.

Thought behind developing JSweet

Cincheo CEO Renauld Pawlak has shed some light behind the reasons for developing JSweet. He stated that in last couple of years TypeScript found widespread usage as it helped in transpiling to JavaScript in an efficient fashion. Java developer were longing for a light and simple approach which can help in designing the Web application in Java with similar efficiency. Most of the developers were frustrated with the idea of running everything in Java on a JRE. While a large number of developers were impressed with what can achieved with distinction through using TypeScript/JavaScript on the front end.

JSweet thus helps in offering a light and simple solution for adding bits of Java syntax to TypeScript. It is a great alternative to the Java developers for developing real Web application with ease.

Java still a great language for developing various apps and programs

Java has been known to cause confusion with its elaborate and complex syntax and functions, which led to the rise in adoption of other coding languages. But Pawlak still considers the Java as a good platform and safer language for the programmers to develop more powerful and rich apps. Java still retains its supremacy in developing efficient and scalable large complex applications than any other language.

JSweet has also made the accommodation for Node.js, which is a popular server side JavaScript platform. Pawlak ahs elaborated that JSweet works in same tandem with Node.js as TypeScript does but the difference is that it adds types. It is a small but quite an interesting difference which it a more transparent way of handling commonjs module for the java programmers.

The benefits and difficulty associated with JSweet

JSweet comes with pre defined @Module annotation, which can be generated automatically when a programmer makes use of the APIs. Here a programmer is just required to import the right packages and that also without the need of knowing all about JavaScript modules.

JSweet is designed to cross validate the Java Programs and the Java API with TypeScript. It also has a JSweet API translator Tool which can make JavaScript APIs available in Java. But Pawlak has the cautioned the programmers from making its wider usage as there are few issues with this technology which needs to be remedied. Pawlak has also asked the Java developer to remain open minded while programming with JSweet as they have to do away with some Java logic.

Moto 360 Sport, Meet Your New Workout Partner

Android Wear market is growing through a crazy phase where every month new wearables are making to the stores and constant innovation is helping in bringing more features to the devices. The latest version of Moto 360 sport shows remarkable improvement over its predecessor Moto 360 in terms of design and features. It is quick and concise of review of the Moto 360 Sport on basis of its first impressions, which is very amazing and impressive.

Moto 360 Sport hardware stands out from the crowd

The Moto 360 Sport comes with integrated silicone band, which is not changeable though. The internals of the Moto 360 Sport 42 mm model is similar to the earlier model with an addition of a GPS receiver. There is new display on this Smartwatch, which is named Motorola AnyLight Hybrid Display technology, which easily adapts with the environment.

It works like a traditional backlit display in low light situation and in the sunlight as front-lit reflective display. Motorola has provided an extended back button, which is located on the upper right side, and mic is located on the lower side. Motorola has carefully positioned the heart rate monitor on the center of the back. Motorola has covered the display with Gorilla Glass 3 surrounded by a ring of metal, which makes it more elegant.

Moto 360 Sport is a performance driven Sartwatch

The Moto 360 Sport runs on the Android Wear 1.3.0.x OS which is based on the popular Android 5.1.1 and it performs flawlessly with no glitches. It has a 300 mAh battery and runs o the 1.2Ghz quad core QUALCOMM Snapdragon 400 processor and has a 4GB of interNal storage with 512 MB of RAM.

Motorola has added some new fitness focused apps as well as a fitness watch face. These apps are called Moto Body and Moto Body Running while the watch face is called Sport, which provides status right in the top of display and a tap for accessing more options.

Users can easily view their heart rate, set goals for various exercises and get some interesting and accurate stats in the results at the end. Moto 360 Sport has a Start button near the middle of the display, which launches the Moto Body Running app where users can select different options before they start their run. Motorola 360 Sport is great at tracking the different exercises along with the calories count burned.

How Moto 360 Sport fares in tests? 

Motorola Moto 360 Sport is very nicely designed and its performance is amazing even though very few tests were performed in short time. First of all this watch is incredibly responsive and it brings one of the best displays ever seen on an Android Wear watch. Motorola 360 Sport will be launching in US In January and it will come with a base price of $299.99. And if you are looking up a smart and a performance driven Android Wear in New Year then keep this watch in your buying list.

How Boring is Your Face? Ask the 'MemNet' Algorithm

Ever thought of knowing how good your face looks in the pictures captured by the selfie cameras. A group of scientists at the MIT’s Computer Science and Artificial Intelligence Laboratory has developed a unique computer algorithm which can easily measure ‘’how memorable an image is’. One is just required to feed the photo from the Instagram feed and the MemNet algorithm will simply show the portion of the images, which are most likely to stick in the memories of viewers. Scientist has even uploaded a version of this algorithm online for everyone to try out.

What is MemNet? 

MmeNet is a deep-learning algorithm, which is designed by the scientist at MIT. Deep learning algorithm is quite hard to develop as they are built to acquire and incorporate new information, which helps in improving their abilities without any manipulation or control of human programmers. Deep learning technologies work in its own unique manner as essentially mimics the neural pathways which area associated with the human learning. This helps deep learning algorithm in repurposing the same logic and understanding for various different skill sets.

MemNet to get better at reading images

MemNet is expected to improve its ability to read images and predict an images’ indelibility by simply processing more and more information over time. These computer scientists have released the MemNet version for the common users to try and with prediction; it will improve its ability of reading faces with more accuracy.

MemNet was first endowed with the basic required skill sets by the MIT scientists through uploading of thousands of images and associated data. The metadata fed to the MemNet basically included the information about each image’s popularity and the emotional impact as determined by the online viewers. When asked to predict the memorable parts within a picture MemNet performed as good as human.

The lead study author, Aditya Khosla, stated that understanding the memorability will help us in making systems, which can capture the most important information, and it can even help in storing the information which are most likely to be forgotten by the humans. Visual images are mostly preferred by a large number of institutions to send across the messages but MemNet can help it making more memorable than before.

Future prospect of the MemNet algorithm

MemNet is not much better at the task of measuring the memorability than any other human but researchers are hopeful it will get better over time. It creates a heatmap to show the memorable part and boring part of each image, which happens to the key elements in understanding the memorability level of the pictures. This algorithm can help the marketers and even the movie makers in editing their images in such a manner than it stays inside the head of the customers and viewers. MemNet can also help people in learning various things easily and efficiently too. People tend to assimilate and forget things more often but the research in developing MemNet opens up a new avenue. It has the potential to improve the people’s memory they are presented with the memorable images.

Facebook’s Artificial-Intelligence Software Gets a Dash More Common Sense

Artificial-Intelligence Researchers – Learn some of the Basic Physical Common Sense

In an attempt to discover how computers could learn some of the basic physical common sense, artificial intelligence researchers have undertaken a project for the same. For instance to comprehend unsupported objects tend to fall or a large object does not fit inside a smaller one, seems to be the main way human tend to predict, communicate and explain regarding the world.

Chief technology officer of Facebook, Mike Schroepfer, state that if machines are to be more useful, they would need the same type of good judgment of understanding. He had informed at a preview recently of results, he would share at the Web Summit in Dublin, Ireland, that they have got to teach computer systems to comprehend the world in the same way. Human beings at a young age, tend to learn the basic physics of reality and by observing the world.

Facebook had drawn on its image processing software in creating a technique which learned to predict if a stack of virtual blocks would tumble. The software tends to study by gaining access to images of virtual stacks or at times two stereo images like those that form a pair of eyes.

Crafting Software – Comprehend Images/Language of Deep Learning

It had been shown in the learning phase, that several various stacks some of which had toppled while the others did not. The simulation showed the learning software the result and after adequate examples, it was capable of predicting for itself with 90% accuracy if a certain stack would possibly tumble. Schroepfer comments that if one runs through a series of tests, it would beat most of the people.

Facebook’s artificial intelligence research group in New York had done the research. It concentrated on crafting software which could comprehend images as well as language utilising a technique of deep learning. Recently the group also showed off a mobile app with the potential of answering queries regarding the content of photos.

The director of the group, Yann LeCun who is also a professor at NYU, informed MIT Technology Review that the system for predicting when block would topple indicates that more complex physical simulation could be utilised in teaching additional basic principles of physical common sense. He added that `it serves to create a baseline if we train the systems uncontrolled and it would have adequate power to figure thing out like that’.

Memory Network

His group had earlier created a system known as `memory network’ which could pick up some of the basic common sense as well as verbal reasoning abilities by reading simple stories and now progressed, in helping in influencing a virtual assistant that Facebook tends to test known as M. M has more potential than Apple’s Siri or similar apps since it is powered by bank of human operators.

 However Facebook expects that they would steadily tend to become less important as the software learns to pitch queries for itself. Schroepfer informs that adding the memory network to M is showing how that could happen. By observing the interactions between people utilising M as well as the responds of customer service, it has learned already how to manage some of the common queries.

Facebook has not made a commitment of turning M into a widely available product; however Schroepfer states that the results indicate how it could be possible. He adds that the system has figured this out by observing humans and that they cannot afford to hire operators for the entire world but with the right AI system, they could organize that for the whole planet.

Gorilla Glass is Making to Cars after Becoming a Dominant Force in Smartphones

Almost every Smartphone nowadays features the Gorilla Glass because of its scratch resistant and strong protective feature. Corning Inc, which is behind the manufacturing of Gorilla Glass has stated that this glass is going to be used in cars after featuring on billions of mobile phones on global scale. Car makers will be making use of Gorilla Glass in order to save weight of their vehicles and to improve the fuel economy.
BMW and Ford set to use Gorilla Glass in cars

Gorilla Glass being used in the car isn’t new as BMW AG was the first car maker to utilize this in the interior panel of the i8 hybrid sports car. Ford Motor Co is all set to use the Gorilla Glass in the windshield and rear window for its upcoming new Ford GT sports car, which will go on sale next year. Ford GT will also feature a Gorilla Glass engine cover.

What makes Gorilla Glass much better than available options? 

The earlier windshields were made up of two layers of specifically heat treated annealed glass and it has a plastic layer in between. Therefore, traditional glass formed the spider web pattern when it broke down and the pieces remain stuck to the plastic layer, which helped in preventing injury to passengers. Gorilla Glass meets U.S. safety standards and it happens to tougher than traditional annealed glass, which makes it an ideal choice for cars.

Exceptions from using this glass

Gorilla Glass is great in every manner but it does have some limitations in usage. Ford won’t be using the Gorilla Glass for the side windows of the GT and it will be made of tempered glass. Automakers have to rely on suing the tempered glass on side windows because it can be breaking into pieces when someone has to exit the car in a crash. Having a Gorilla Glass will mean adding a layer of plastic over the glass, which will turn it into unbreakable, which can put people lives in danger during crash. However the business director of Corning’s automotive glass business has stated that they are working on a different version of Gorilla Glass which be used throughout the vehicle.

Everything isn’t in favor of Gorilla Glass

Gorilla Glass has been used in the consumer electronics since 2007 and Corning made its foray in the automotive glass in 2012. In order to meet the stricter fuel economy standards several automakers are looking at various options to reduce weight in cars. Weight happens to be the enemy of the car, which seriously hampers the process of reaching awesome fuel economy in automobiles. Corning Glass does offer help in saving weight but it is quite expensive than the traditional glass. Gorilla glass costs $2 to $4 more per pound in weight than the traditional glass. To summarize Ford will be able to save 12 pounds on GT, which will mean spending $12 to $48, more on the car. An expensive car like GT which comes at price tag of $400,000 can easily absorb this expensive but mainstream car can’t.