libGDX Jam - Powered by RoboVM & Robotality - itch.io Latest Dev Logs The 10 Rules of Jamming You must use libGDX to create the game Your game must fits the theme You may work alone or in a team. Only one submission per person/team is allowed You may use pre-existing code, e.g. libraries like Ashley, or your own code libraries You may use pre-existing art, e.g. assets from OpenGameArt, or your own art You may use external tools like Tiled or Overlap2D, or anything alike You must not re-skin an already existing game or prototype!
Modules · joyent/node Wiki This page is deprecated. Feel free to add to it, but be advised that it is, at best, a faded relic of Node modules that were written before npm was a dominant force in the Node.js ecosystem. It is not all that useful any more. If you are a newcomer, it can be handy to at least get a starting point. Meteor Simplest example. A live-updating high score list. Try it yourself In about 3 minutes, you'll make your own copy of Leaderboard and deploy it live on the Internet for you and your friends to use. No programming knowledge required! Actualité LibGDX Kek or how I’ll waste my free time going forward Mario, Thu, 30 Jun 2016 15:09:21 -0700 It’s been a while since this blog had anything other to offer than “libGDX x.x.x released”. This was partly a result of my engagement with RoboVM, which, as you may have heard, is no more. And while I got plenty of real-world-ish stuff to do going forward, I also feel in need of something to challenge my old-farty brain a little in my spare time. For bonus points, I’d like to share my insights and failures with you.
Node.js vs PHP: Visualize node.js efficiency with Load Impact It could be said that Node.js is the new darling of web server technology. LinkedIn have had very good results with it and there are places on the Internet that will tell you it can cure cancer. In the mean time, the old work horse language of the Internet, PHP, gets a steady stream of criticism. and among the 14k Google hits for “PHP sucks” (exact term), people will say the most funny terrible things about the language while some of the critique is actually quite well balanced. Node.js introduces at least two new things (for a broader audience).
Asynchronous Component-Based Programming It seems hardly worth pointing out that the universe we live in is a highly asynchronous place: it is a place where an infinite number of things are happening all at once. In fact, it might be said that humans, and indeed all living creatures, are designed to operate in such an environment. In spite of this, until recently, computer programs were always based on the model of a sequential, "one step at a time", computer with a single instruction counter. Not surprisingly, therefore, mapping the real world onto such a model has always been difficult, and is becoming more so as the requirements on our systems become ever more stringent impress Impressive totalitarian style Multipurpose Application Server for node.js. All decisions are made. Solutions are scaled.
Setting Up a MEAN Stack Single Page Application Beginning an application from scratch can sometimes be the hardest thing to do. Staring at an empty folder and a file with no code in it yet can be a very daunting thing. In today’s tutorial, we will be looking at the starting setup for a Node.js, AngularJS, MongoDB, and Express application (otherwise known as MEAN). I put those in the wrong order, I know. This will be a starting point for those that want to learn how to begin a MEAN stack application. Projects like mean.io and meanjs.org are more fully fledged MEAN applications with many great features you’d want for a production project. Caffe2 : The Deep Learning Framework for Mobile Computing Short Bytes: Caffe2 is Facebook’s new Open Source Deep Learning Library. In contrast to its previous PyTorch library, Caffe2 is built especially for bringing Deep Learning to Mobile Applications. Our Smartphones are gonna get more “Deeply” smarter soon!!. If you think Deep Learning is just about math, you are gravely mistaken. Various research labs across the world try to develop efficient and fast software frameworks that enable the researchers or the general public, to implement and test the Deep Learning models.