It was a miniscule change in parameters – just 2mm – but that tiny deviation delivered to a real robot in a recent hacking experiment could result in a massive product recall or even a major defect in an aircraft design in a real manufacturing scenario. Researchers at Trend Micro and Italy-based Politecnico di Milano today detailed the proof-of-concept attack they conducted on an ABB Robotics IRB140 industrial robot, exploiting a remote code vulnerability they found in the robot's controller software. They fed the robot a phony configuration file that modified its parameters for drawing a straight line. Instead of a perfectly straight line, the robot drew a slightly skewed one, following the 2mm change in instructions. "The code was working as expected, but with the wrong configuration," says Mark Nunnikhoven, Trend Micro's vice president of cloud research.

Who's going to be the next Mobileye? Computer vision is a hot topic for the tech industry, and especially in Israel. It seems like Israeli entrepreneurs are one step ahead when it comes to developing computer vision technology. That's why we're excited to announce that three computer vision experts are going to join us on stage to share their knowledge about this space. First up, Inon Beracha has become a well-known name in Israel.

John Wanamaker, who opened his department store in a Quaker district of the city, introduced price tags for his goods, along with the high-minded slogan: "If everyone was equal before God, then everyone would be equal before price." Up until then high-street retailers had generally operated a market-stall system of haggling on most products. Their best prices might be reserved for their best customers. Or they would weigh up each shopper and make a guess at what they could afford to pay and eventually come to an agreement. Wanamaker's idea was not all about transparency, however.

Barbara is Co-Founder and CEO of the Chatbots Agency, a software development and consulting company based in Vienna, Austria. Mica, the Hipster Cat Bot Mica, helps you discover the best places worldwide. It was the first chatbot ever created for Messenger in Austria, was also one of the very first chatbots on the Facebook Messenger and Skype platform -- and is still the top 7 bot on Skype. Besides that Mica is also available on Kik, Telegram and Viber. In March Mica reached 100.000 unique users that have been chatting with her.

Edgar van Tuyll van Serooskerken, head of Quantitative Strategies at Pictet Wealth Management, explains how Pictet uses machine learning for two purposes: first, to hunt for profitable investment opportunities; and second, to search for patterns in big data that are similar to those of past periods. For the first use, machine learning can sift through the mass of data we now have on the past prices of assets in various classes, on company performance and on macro-economic developments, in order to look for hidden treasure. It will hunt for relationships between data points that could allow us to make returns and we study them with our experts to see if they make sense – we don't just trust the machine and trade off them. Nonetheless, since 2013 we have come up with a whole series of automated strategies, which have beaten the hedge fund index by a wide margin. They tend to reflect human behaviour which doesn't change very much and makes those strategies stable for long periods.

Kai-Fu Lee sees America as destined to lose to China in the race for leadership in AI. Kai-Fu Lee watched the U.S. beat China to global internet leadership during the dot-com bubble from the inside. Now with what he sees as an even greater technological revolution taking place in the fast-growing field of artificial intelligence, Lee doesn't expect China to take a backseat a second time. "China started slow, and American companies went international," Lee says during a May visit to Forbes Media's headquarters. "But simple math says China has a larger GDP. The market will be bigger."

Outside of Data science, I also co-founded a social enterprise to teach Computer Science to kids Feynlabs. At Feynlabs, we have been working with ways to accelerate learning to Code. One way to do this is to compare and contrast multiple programming languages. This approach makes sense for Data Science also because a learner can potentially approach Data science from many directions. To learn programming for Data Science, it would thus help to build up from an existing foundation they are already familiar with and then co-relate new ideas to this foundation through other approaches. From a pedagogical standpoint, this approach is similar to David Asubel who stressed the importance of prior knowledge in being able to learn new concepts: "The most important single factor influencing learning is what the learner already knows."

Seated on the patio of Mission Heirloom in the Gourmet Ghetto, Mason, 42, still jetlagged from his return from a writers' retreat in Tuscany, relents a bit when pressed for elaboration. "I hate describing it," he says. "But when forced, I say it's a combination between Mrs. Dalloway and Neuromancer ." That's an elevator pitch that actually says something meaningful. Published by Farrar, Straus & Giroux on April 11, Void Star follows three disparate characters as they navigate a Future world altered by climate change, social inequality, longevity extension, digital brain implants and the machinations of incredibly powerful artificial intelligences.

Another big part of the food supply comes from ranches and farms that raise and slaughter various livestock. While ranching is sometimes bundled with agriculture, I discussed farming in Big Data in Agriculture, so we'll focus on ranching this time around. Somewhat surprising is that big data usage in ranching appears more limited than in farming. That said, there are a number of novel uses of technology and data in animal husbandry. At a high level, the goals of ranching and farming are the same as any business: increase yields and lower costs. Production maximization has long played a role in large operations.

The global text analytics market size is estimated to grow from $3.97 billion in 2017 to $8.79 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 17.2%. The customer experience management (CEM) is expected to hold the largest market share during the forecast period. Among the various applications in the text analytics market, the CEM application is expected to hold the largest market share during the forecast period. Text mining is the most traditional application in customer service and is frequently utilized to improve customer experience through various information sources. Today, text analytics is implemented to offer quick, computerized feedback to the clients, which significantly reduces dependency on executives for resolving issues.