What if robots could be powered by light instead of bulky battery packs or movement-limiting power cables? That's the scenario that scientists at the University of Warsaw are envisioning. Researchers have developed a half-inch-long so-called soft robot that mimics the movements of a caterpillar. It's powered by light and controlled by a laser beam, according to the university. "Designing soft robots calls for a completely new paradigm in their mechanics, power supply and control," said Piotr Wasylczyk, head of the Photonic Nanostructure Facility at the University of Warsaw, in a statement.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Salesforce.com Inc. CEO has revealed the company is building a new artificial intelligence (AI) product called "Einstein," in a lengthy interview with Forbes. The article says that Salesforce's Einstein project is the reason why the company decided to shell out a massive 390 million to acquire responsive-email firm Relate IQ and its CEO Steve Loughlin almost two years ago. In addition, the project also explains why Salesforce has acquired no less than six AI-related startups in the last couple of years. "If this is not the next big thing, I don't know what is," Benioff told Forbes' writer Alex Konrad. The article portrays Benioff as a highly successful and hyper-energetic CEO who's built one of the fastest growing and most innovative tech firms around, seeking new innovation to drive the next stage of the company's growth.

Facebook is open sourcing a set of computer vision software tools that can identify both the variety and the shape of objects within photos. The tools, developed by the Facebook AI Research (FAIR) team, are called DeepMask, SharpMask, and MultiPathNet, and all three work in tandem to help break down and contextualize the contents of images. These technologies, though not in active use in consumer Facebook products right now, are similar to the software the company uses to describe photos to blind users, a feature it calls "automatic alternative text" that launched back in April. DeepMask and SharpMask are more experimental research projects and focus on what the FAIR team calls segmentation. While human beings can discern the various elements of a photograph in mere seconds, the process is much harder for computers, which perceive pixels as a series of number values corresponding to changes in color.

The future of Education is always a hot topic anywhere in the globe, as we universally want the best for the next generation. As I get older, I see a rapidly growing gap between how I learnt at school and at University, and what the current working world expects. Recently, I was on a speaking panel for a conference about Emerging Trends in Learning and working tackling the practical impacts of the digital disruption starting to hit the Education sector. Greg Prior from NSW Education, drove the point that literacy and numeracy are still a fundamental core. Collaboration and personalised learning is emerging as a key approach and governments will allow students to progressively take leadership of their own learning.

Not all robots are metal monstrosities with unchecked artificial intelligence that could jeopardize mankind's future. Meet Octobot, a 3D-printed autonomous soft robot out of Harvard crafted exclusively of flexible parts. Harvard calls Octobot "the first autonomous, entirely soft robot." Its squishy-looking tentacles wiggle and dance thanks to a microfluidics-controlled chemical reaction that turns hydrogen peroxide into gas that flows into the octobot's arms, inflating them like a balloon. The tentacled robot is inspired by real-life octopi.

As more cyber-security threats arise every day, extensive research into prevention and detection schemes is being conducted globally. One of the issues faced is keeping up with the sheer mass of new emerging threats online. Traditional detection schemes are rule or signature based. The creation of a rule or signature relies on prior knowledge of the threats structure, source and operation, making it impossible to stop new threats without prior knowledge. Manually identifying all new and disguised threats is too time-consuming to be humanly possible.

How much can a 17-year-old boy really know about women? For starters, that thousands face heartbreaking and costly misdiagnosed breast cancer scares every year. Abu Qader, who's about to start his final year in the Chicago public school system's Lane Technical College Prep High School, was born in war-scarred Afghanistan but has spent most of his 17 years on Earth in the U.S. Qader and European business partner Vedad Mesanovic, who focuses on young and under-resourced scientists, created a company they call GliaLab (named after the cells that support and protect neurons). They are now courting venture capitalists for a targeted 600,000 to help finance the breast cancer-focused artificial intelligence that Qader first created for a 10th-grade class project. Qader believes his technology can help women (and men, too) take on potentially deadly breast tumors and non-cancerous growths by using the convenience of their own mobile phone or tablet to aid in diagnosis and classification, reduce human error and save the expense of false-positive readings.

Mediaplanet today announces distribution of its first edition of "Future of Business Technology," out in The San Francisco Chronicle as well as online. The world as we know it is run by technology. Siri manages day-to-day schedules, robots vacuum floors, Instagram suggests videos one might like and cars can self-park. Despite movies like "The Terminator" and "I, Robot," which suggest robots can only take over the world, the truth is, they're here to stay and here to help. This campaign aims to advocate for the disruptive technologies and solutions like artificial intelligence, robotics, cybersecurity, big data and Internet of Things.

Zero-Shot learning has been shown to be an efficient strategy for domain adaptation. In this context, this paper builds on the recent work of Bucher et al. [1], which proposed an approach to solve Zero-Shot classification problems (ZSC) by introducing a novel metric learning based objective function. This objective function allows to learn an optimal embedding of the attributes jointly with a measure of similarity between images and attributes. This paper extends their approach by proposing several schemes to control the generation of the negative pairs, resulting in a significant improvement of the performance and giving above state-of-the-art results on three challenging ZSC datasets.