Do you get squeamish when someone dies on Game of Thrones? Or maybe you're worried your favorite character is about to get killed, and you can't bear to watch. Researchers at MIT have developed an algorithm that can predict what's going to happen next in a video, giving you an opportunity to look away first. The algorithm, developed at MIT's Computer Science and Artificial Intelligence Laboratory, is slowly trying to learn a skill that humans spend their entire lives refining and perfecting. Through countless interactions and experiences with others, we're able to accurately predict what will happen when two people meet or depart--be it a handshake, a hug, or a kiss.

Keras is a simple and powerful Python library for deep learning. Given that deep learning models can take hours, days and even weeks to train, it is important to know how to save and load them from disk. In this post you will discover how you can save your Keras models to file and load them up again to make predictions. Save and Load Your Keras Deep Learning Models Photo by art_inthecity, some rights reserved. Model weights are saved to HDF5 format.

Big data has already made fundamental changes to the way businesses operate. There are huge advantages for companies who can derive value from their data, but these opportunities come with challenges, too. For some, this is the challenge of acquiring data from new sources. For others, it is the task of building a scalable infrastructure that can manage the data in aggregate. For a brave few, it means extracting value from the data by implementing advanced analytic techniques and tools.

From ISC 2016 in Frankfurt, Germany, this week, Intel Corp. launched the second-generation Xeon Phi product family, formerly code-named Knights Landing, aimed at HPC and machine learning workloads. The company had been shipping "Knights Landing" silicon to early customers for the last six months and was waiting to ramp up production before making the product generally available. The window also gave OEMs time to complete their readiness, said Intel's Charlie Wuischpard, vice president of the Data Center Group and general manager of High Performance Computing Platform Group, in a media pre-briefing. Those OEMs include the usual names: Cray, HPE, Lenovo, Dell and others. The most distinguishing feature of the chip is that it's a bootable host CPU -- unlike its predecessor "Knights Corner," which is a coprocessor that connects over PCIe.

Virtual reality and AI has entered the global workforce at an alarming rate. There are many talented and qualified individuals that enter the job market of VR, however, they are easily replaced by the very technology that created the job later in the game. The idea is to get the VR information out to as many people as possible with the use of things like inexpensive headphones and various picture taking and video initiatives. These advertising experiences have even taken place at popular gatherings, like comic-con. The goal is to reach as many people as possible through various video outlets like YouTube etc.

Industrial robots used to be big, unwieldy, and dangerous, but new "human-safe" robots are now commonplace on automotive lines, working right next to people. Yet these robots are awkward coworkers; they coexist with us but do not meaningfully collaborate. Robots often need to be explicitly told how to be helpful or when to stay out of the way -- things human teammates seem to learn intuitively. A good human apprentice is a keen observer, inferring unspoken rules and customs, watching how others work, and then generalizing this knowledge for new situations. We are able to accomplish this partly because the human mind is able to process very complex information very efficiently.

Are artificial intelligence (AI) and predictive analytics just the latest trendy buzzwords, or is the technology about to transform the enterprise? We spoke to IBM, Microsoft, Insidesales.com, Google and SAP to find out. The world's biggest tech companies are investing heavily in artificial intelligence (AI): software that can learn to think and solve problems in a human-like way. According to Deloitte: "By end-2016 more than 80 of the world's 100 largest enterprise software companies by revenues will have integrated cognitive technologies into their products."

We are all familiar with the doomsday scenario depicted by many modern films, when artificial intelligence goes bad and takes over the world. But this is not going to happen, according to Google chairman, Eric Schmidt, who claims that super-intelligent robots will someday help use solve problems such as population growth and climate change. During a talk in Cannes, he said AI will be developed for the benefit of humanity and there will be systems in place in case anything goes awry. Artificial intelligence will let scientists solve some of the world's'hard problems.' During a talk in Cannes, Eric Schmidt said AI will be developed for the benefit of humanity and there will be systems in place in case anything goes awry. 'We've all seen those movies,' he said.

Twitter today is taking another step to build up its machine learning muscle, and also potentially to improve how it delivers photos and videos across its apps: the company is acquiring Magic Pony Technology (that is really the name), a company based out of London that has developed techniques of using neural networks (systems that essentially are designed to think like human brains) and machine learning to provide expanded data for images -- used, for example, to enhance a picture or video taken on a mobile phone; or to help develop graphics for virtual reality or augmented reality applications. Terms of the deal are not being disclosed but we have two separate sources who tell us that Twitter is paying 150 million in all for the deal. This takes into account retention bonuses for the staff, which numbers about 11, including co-founders Zehan Wang and CEO Rob Bishop. "Machine learning is increasingly at the core of everything we build at Twitter," said Jack Dorsey, Twitter CEO and co-founder, in a statement. "Magic Pony's machine learning technology will help us build strength into our deep learning teams with world-class talent, so Twitter can continue to be the best place to see what's happening and why it matters, first. We value deep learning research to help make our world better, and we will keep doing our part to share our work and learnings with the community."

WWDC16 just ended and Apple left us with new amazing innovative APIs. This year speech recognition, proactive applications, deep learning, user intents, and neural networks have been the most frequent terms used during the conference. So, besides a new rich version 3 of Swift, almost every new addition to iOS, tvOS and macOS is related with artificial intelligence. For example, Metal and Accelerate in iOS 10 provide an implementation of convolutional neural networks (CNNs) for the GPU and CPU respectively. During the keynote, Craig Federighi (Apple's SVP Software Engineering) showed how the Photos app on iOS organizes our photos according to different smart criteria. He highlighted that Photos app uses deep learning to provide such functionality. Also, Federighi showed how Siri, now available to developers, can suggest what we need.