A town in the Netherlands is trialling special pavement lights designed to help smartphone users cross the road safely. The LED strips have been embedded into the ground at a pedestrian crossing in Bodegraven, close to three schools. The hope is that they'll catch the eye of pedestrians who are too distracted by their smartphones to bother looking at the road, telling them when to cross and when not to cross by either glowing green or red, depending on the traffic light signals. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar. Japan's On-Art Corp's CEO Kazuya Kanemaru poses with his company's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' and other robots during a demonstration in Tokyo, Japan Japan's On-Art Corp's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' performs during its unveiling in Tokyo, Japan Singulato Motors co-founder and CEO Shen Haiyin poses in his company's concept car Tigercar P0 at a workshop in Beijing, China A picture shows Singulato Motors' concept car Tigercar P0 at a workshop in Beijing, China Connected company president Shigeki Tomoyama addresses a press briefing as he elaborates on Toyota's "connected strategy" in Tokyo.

What supercomputers will look like in the future, post-Moore's Law, is still a bit hazy. As exascale computing comes into focus over the next several years, system vendors, universities and government agencies are all trying to get a gauge on what will come after that. Moore's Law, which has driven the development of computing systems for more than five decades, is coming to an end as the challenge of making smaller chips loaded with more and more features is becoming increasingly difficult to do. While the rise of accelerators, like GPUs, FPGAs and customized ASICs, silicon photonics and faster interconnects will help drive performance to meet many of the demands of such emerging applications as artificial intelligence and machine learning, data analytics, autonomous vehicles and the Internet of Things, down the road new computing paradigms will have to be developed to address future workload challenges. Quantum computing is among the possibilities being developed as a possible solution as vendors look to map out their pathways into the future.

Chatbots look likely to be a cornerstone of many brands' marketing campaigns this year with the programs capable of generating automated engagement with consumers. Able to sit within messaging apps and communicate when prompted, chatbots can serve a wide variety of roles; the Guardian is distributing news; Activision engaged fans with the Call of Duty Series, Domino's Pizza is accepting food orders, and KLM's flight assistant houses boarding pass and flight times. For creative brands with on tap digital talent, the sky's the limit. The Drum has touched down with Paul Walsh, the founder of bCRM, a chatbot campaign management tool, which is now integrated with BotKit, one of the most widely used bot creation tools, to outline the basics for prospective brands. The Drum: What benefits can chatbots bring to consumers?

IBM has announced the launch of IBM Machine Learning, a cognitive platform for the z System mainframe. The new platform uses the core technology from IBM Watson to perform big data analysis for clients using z System for cloud data storage. The new Machine Learning platform automates the creation and deployment of analytic models, allowing data scientists to perform analysis in-house. Models can be written in any language (Scala, Java, Python), using any framework and data type required for best results. IBM Machine Learning also includes a function called Cognitive Automation for Data Scientists, which helps data scientists to choose the correct algorithm for their needs.

First you do not always need to normalize (standardize) the input vectors (feature vectors), sometimes is good, sometimes is bad. In general you scale your feature vector when the magnitude of a feature dominates the others, so the model cannot pick up the contribution of the smaller magnitude features. Read here for a detailed explanation. Second there are two general classes of machine learning problems: classification and regression. In a classification type problem the output (dependent variable) is discrete, so you do not need to normalize it.

Microsoft Corp. is trying again in health care, betting its prowess in cloud services and artificial-intelligence can help it expand in a market that's been notoriously hard for technology companies. A new initiative called Healthcare NExT will combine work from existing industry players and Microsoft's Research and AI units to help doctors reduce data entry tasks, triage sick patients more efficiently and ease outpatient care. "I want to bring our research capabilities and our hyper-scale cloud to bear so our partners can have huge success in the health-care world," said Peter Lee, a Microsoft Research vice president who heads Healthcare NExT. Microsoft has tried to expand in health care before, with mixed results. It had a Health Solutions Group for many years, but combined that into a joint venture with General Electric Co.

As consumer devices become more capable, with voice control assistants such as Apple's Siri, Amazon's Alexa, Microsoft's Cortana and Google's Assistant, it is only natural to expect these artificial intelligence (AI) applications to move into more business settings. These capabilities could emerge in a number of areas, such as voice control-style interfaces on common productivity applications and voice output to warn IT managers of potential infrastructure faults or breaches. This makes sense -- after all, there is already an AI-enabled toothbrush that learns exactly how you clean your teeth and offers ways to improve your dental hygiene. It is just a matter of time before major industry players develop B2B apps with similar smart features. Today, voice-enabled products can be used for mundane tasks, such as dictating emails or text messages, querying internet searches or playing music and TV shows.

NEW YORK--Are you ready to turn your car, washing machine or running shoes into a point of sale? Visa is teaming up with IBM Watson to bring secure payment experiences to all sorts of connected products and services, embracing the ecosystem techies inelegantly refer to as the Internet of Things. IBM and Visa announced the collaboration Thursday at an event in Munich, Germany, where IBM is opening up a $200 million Watson Internet of Things headquarters. Via the partnership, the companies say they can support payments and commerce on virtually any of the 20 billion connected devices that Gartner estimates to be part of the global economy by 2020. "What we've seen over the last 12 months is serious companies committing serious business to IoT," says Brett Greenstein, vice president for IBM Watson IoT. Watson is IBM's cognitive computing platform, which leverages natural language processing and machine learning to learn from and extract patterns and meaning from mounds of unstructured data, from health care to sports.

For decades, data and analytics have played an important role in our economy. The process of analyzing data, however, remains labor intensive. Even with the most advanced techniques, data scientists spend countless hours developing, testing and retooling analytic models one step at a time. Worse yet, most organizations cannot find enough data scientists to complete this labor-intensive work. The impact is that we have not yet fully realized the promise of continuous intelligence; until now.

As machine learning becomes more accessible through avenues such as Intel's BigDL and IBM opening Watson's core machine learning components up to businesses, some developers and industry insiders are cautioning against getting too dazzled by the potential without considering the human role. However much data those programs can process, in the end, "what you do with the results of algorithms is key," said Jean-Francois Puget, Ph.D. (pictured), distinguished engineer, machine learning and optimization, IBM Analytics, at IBM. Puget spoke with Dave Vellante (@dvellante) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media's mobile live streaming studio, at the IBM Machine Learning Launch Event in New York, NY. He offered his perspective on machine learning and its applications. "For most people, machine learning equals machine learning algorithms," Puget said. "When you look at newspapers or blogs, social media, it's all about algorithms. Our view [is] that sure, you need algorithms for machine learning, but you need steps before you run algorithms, and after."