For the last five years, IBM has strived to reinvent itself as a cloud computing and cognitive platform company to support its large enterprise clients as they shift their operations online, including many in travel and transportation. With most large companies today evolving into digital companies, cloud computing is a booming marketplace for the big four industry providers: IBM, Microsoft, Google, and Amazon. Google, for example, stated that cloud could overtake advertising revenue in five years. Travel companies like Etihad and Lufthansa are helping drive IBM's cloud sales. The UAE carrier signed a 700 million IT deal with IBM last October, while Germany's national airline invested 1.25 billion in Big Blue in November 2014 to integrate cloud computing.

Angela also leaves behind her beloved companion, Eric Dunbar of Vinton and his children, Erica, Jonathan, Patrick and Kristen.She will be remembered as a beloved mother, sister, daughter, partner, and friend to countless others.Funeral services will be at 3 p.m. on Wednesday, March 30, 2016, conducted from Conner-Bowman Funeral Home with Pastor Rick Poland officiating.Arrangements by Conner-Bowman Funeral Home, 62 Va.

In two previous posts, I covered the emerging industry of cloud-based machine learning solutions. First, I covered Microsoft's Azure Machine Learning and IBM's Watson Analytics. Microsoft's Azure ML provides a graphical drag-and-drop interface for connecting preprogrammed components of a data science pipeline together. The service is similar to KNIME and seemed targeted for users who knew just enough to know what to do, but not so much that they would want to code up fresh algorithms. One value added for Microsoft's product is a smooth integration for companies which already have their data stored in Microsoft's Azure compute cloud.

"Cognitive conversations" with artificial intelligence are "the future" of customer care, IBM's CTO of Watson Europe reckons. Speaking at Computing's Big Data and Analytics Summit 2016 last week, Duncan Anderson explained how AI like IBM Watson is "not Ex Machina" - referring to the 2015 film in which human-like AIs become self-aware - but is now at the point where it can soon make considerable changes to the daily lives of people. "The practical reality of where we are is not Ex Machina - we're not building beautiful computers and spoofing humans, [but] we're solving practical problems today," he said. Anderson said Watson's growing ability to process unstructured data - "text documents, images, voice - the novel data types" - is now bringing to an end the traditional approach of putting such data "in a database clock and [doing] nothing with it". While this is nothing new, Watson's improving effectiveness at communicating what it's learning back to a user in the form of "chat" is now becoming an increasingly viable frontline tool.

Watson, the name for IBM's supercomputer best known for crushing '"Jeopardy!" contestants at their own game, briefly went from "smart" to "smart ass" with the help of the Urban Dictionary. According to Eric Brown, an IBM research assistant and the "brains" behind Watson, he and his 35-person team wanted to get IBM's supercomputer to sound more like a real human. In Brown's mind, what better way to learn the intricacies of informal human communication and conversation than having Watson memorize the Urban Dictionary? The Urban Dictionary, for those who don't know, is comprised of submissions from everyday people and regulated by volunteer editors, who are given an extremely small set of rules to maintain quality control. But for the most part, even with the help of human editors, the Urban Dictionary still turns out to be a rather profane place on the Web.

You may know Watson for its ability to dominate Jeopardy, but did you know it has impressive movie skills too? IBM has hinted at Watson's movie-watching capabilities, like in its commercial with film director Ridley Scott, but we've never seen it in practice. So we asked Watson to tell us what it thought of the "Harry Potter" original book series and movies -- and the results are really interesting. By analyzing written text, Watson can identify different tones such as fear, joy, confidence, and openness. It can also analyze written text to assess personality traits based on the Big Five test, one of the most common, preferred ways psychologists use to measure personality.

IBM has updated its artificial intelligence (AI) product, IBM Watson, giving it the ability to recognise images. Watson, which relies on cognitive learning to help it process the world in a human-like manner, can now'guess' what's happening in images fed to it via URLs. IBM has created a'Visual Recognition Demo' to showcase Watson's latest trick, which allows users to feed Watson an image before it tells you what it believes it sees. For example, supplying Watson with the image of a tiger throws up the result 77 per cent tiger, 26 per cent wild cat and 63 per cent cat. As well as identifying objects, people or animals in photos, Watson is also fairly adept at guessing what's going on in the background of images such as sunsets and other outdoor scenes.

Former top executives from IBM Watson, GE Digital, Infosys and MicroStrategy announced last week that they have joined forces with TPG Growth to launch Noodle Analytics, Inc., the Enterprise Artificial Intelligence company. Enterprise AI represents a major step forward in merging human learning and machine learning, all fueled by big data. Enterprise AI solutions combine expertise in human-centered design, business process engineering and artificial intelligence technologies. Today's artificial intelligence technologies include machine learning, predictive data analytics and data science. "Over the next three to five years, artificial intelligence technologies and big data will be the most significant competitive differentiators in business.

Today, we create a staggering amount of information: formulas, tweets, poetry, photos, videos and many more. Even our discoveries and diagnosis generate data. Can we draw meaning from it? Overcome obstacles that used to stop us. Spot diseases before patients display symptoms.