Gartner tracks emerging technologies in its annual Hype Cycle reports that enable organisations to increase this interconnection, allowing for the real-time exchange of vast quantities of data, and for increased intelligence, complex analysis and decision making in real time. To help IT leaders understand significant technology trends, Gartner analysts looked across all 109 Hype Cycles and noted four high-level megatrends trends that track the evolution of digital business technologies, services and business models. "New digital business models require ecosystems of people, businesses and technologies that must scale beyond the enterprise," said Betsy Burton, vice president and distinguished analyst. Since 2008, cloud, data, mobile and social (the Nexus of Forces) have dramatically affected people's lives, business interactions, social change and global economies. These massive collections of technologies and the resulting changes in business models and human behaviour have accelerated the interconnection of technology, business and humans, and given rise to digital business.

BOSTON: Artificial Intelligence (AI)-powered bots will become the next interface, shaping our interactions with the applications and devices we rely on and Microsoft's latest solutions are set to change the way HP interacts with its customers and partners, Indian-born Microsoft CEO Satya Nadella has said. "Bots are now learning in human context and the relevant thing for us is to make them intelligent as we learn from customers' experience. Our solutions are going to give HP a 360-degree view of its customer services," Nadella announced at HP's Global Partner Conference (GPC) 2016 at the Boston Conference and Exhibition Centre (BCEC) here. HP announced a six-year agreement to deploy Microsoft Dynamics customer relation management (CRM) online in order to enhance collaboration across marketing, sales and service operations. With Dynamics, as well as Azure, Office 365 and other Microsoft Cloud solutions, HP has invested in the sales and service collaboration platform to deliver a seamless sales experience for customers and partners.

An hour before dawn today, Uber hit the green light on a project that many here have seen, but never experienced. Some of Uber's heaviest users will wake up to an email Wednesday inviting them to test out the company's new self-driving cars, the centerpiece of a fully autonomous fleet Uber plans to use in the long run to replace human drivers. The pilot project, which is the first in the United States to include members of the public, offers a taste of a technological future thousands have only read about. Do these cars really work? Judging by an early demo that Uber provided to reporters this week, the answer is yes -- at least under ideal conditions.

Specialized dictionaries are used to understand concepts in specific domains, especially where those concepts are not part of the general vocabulary, or having meanings that differ from ordinary languages. The first step in creating a specialized dictionary involves detecting the characteristic vocabulary of the domain in question. Classical methods for detecting this vocabulary involve gathering a domain corpus, calculating statistics on the terms found there, and then comparing these statistics to a background or general language corpus. Terms which are found significantly more often in the specialized corpus than in the background corpus are candidates for the characteristic vocabulary of the domain. Here we present two tools, a directed crawler, and a distributional semantics package, that can be used together, circumventing the need of a background corpus.

Big Data Learning in Practice This page has been created to provide information about the talk entitled: "Big data Learning in Practice" given at Benelearn 2016: https://www.kuleuven-kulak.be/benelearn/index.html Abstract Extracting valuable knowledge from big data datasets by means of machine learning techniques may result in more accurate models than ever before. However, most of the standard methods fail to tackle the new space and time requirements. Fortunately, the leverage of recent advances achieved in distributed technologies enables machine learning techniques to discover unknown patterns or hidden relations from voluminous data in a faster way. Nevertheless, the issues posed by (real-world) complex data go beyond computational complexity, and big data mining techniques are confronted with multiple challenges w.r.t. In the first part of this talk I will provide a brief introduction to the big data problem, including MapReduce, as the most representative programing paradigm, as well as a quick overview of recent technologies (Hadoop ecosystem, Spark).

This car was designed by a computer, inside a virtual environment. A startup called Hack Rod used Nvidia GPU technology and Autodesk software to use AI to design a car. Autodesk's Dreamcatcher let them use "generative design," in which the computer iterates on ideas that the designers input. In this case, Hack Rod wanted to create an optimized hot rod, and used Autodesk Flow Analysis to perform aerodynamic testing and quickly iterate many chassis designs. The software replicated sensors that could give feedback on how the design would perform under pressure, running several digital test drives.

Experts discuss the costs and benefits created by developments brought on by Artificial Intelligence. In recent years, Artificial Intelligence (AI) has established itself at the forefront of technological innovation. That is precisely why AI is the focus of the Hot Topic at the 4th Heidelberg Laureate Forum (HLF), 'AI: From Lofty Dream to Technology Driver', this September 20 at the New University in Heidelberg. The session is comprised of a panel discussion with leading researchers debating the current scientific trends in AI and its applications. That is followed by a broader discussion that dives into how the developments in AI affect our lives and society.

Peter's review of the landscape suggests that over the past few years, a largely unheralded energy revolution has quietly got under way: that the feedback loops that have kept fossil fuels strong, and renewables weak, are undergoing a reversal. With renewables ascendant, and fossil fuels on the brink of a public opinion pivot akin to the one experienced by the tobacco industry a decade ago, what can we expect from the energy landscape of 2020? The Reinventing Energy Summit will explore the opportunities of applying AI and machine learning techniques to efficiently manage energy generation and consumption; predicting energy supply; smart grid management and operations; intelligent control of energy storage; batteries, and much more.

Slaughter and May has signed a deal to use a new artificial intelligence (AI) system called Luminance which it helped create with backing from a technology investment company set up by Autonomy co-founder Mike Lynch. The firm worked closely with Luminance Technologies, which has been funded with capital from Invoke Capital, for several months to test and pilot the software Luminance claims will transform the due diligence process on M&A deals. The elite magic circle firm is the only law firm to have piloted Luminance prior to its launch, though several others are also interested in piloting the technology. Its expertise on deals and due diligence was used to help improve the technology. Slaughters has signed a contract to use the technology going forward, though the details around this are not yet clear.

Nvidia Corp. announced new processors Monday to try to embed its products in artificial-intelligence systems that are increasingly becoming part of daily life. The chipmaker, which dominates in video gaming, rolled out graphics chips for running software that makes split-second decisions needed when everything from phones to cars to internet search engines respond to inputs such as speech, images and moving objects. The company said its new Tesla P4 chip is for servers used in massive data centers. Based on its Pascal design, the P4 is more than three times as efficient at processing images than its predecessor and 40 times more efficient than Intel server chips, according to Nvidia. Another new chip, called the P40, is designed for more-powerful single computers, such as supercomputers.