Artificial Intelligence (AI) is gathering pace as one of the biggest ICT trends of our time – and the topic of "robot journalism" provides important insight on how AI is being applied to industry. How is natural language generation (NLG) being used to explain big data in narrative form that broader audiences can easily understand? What insights are being found by machines producing 2,000 articles per second? How are some of the world's biggest media agencies currently using vendors that provide these solutions to build their reach, engagement, and businesses? Will "robots" (or automated content) soon render journalists obsolete?

Hisashi Taniguchi used a sabbatical from developing software for driverless taxis and drones to take a pilgrimage to a Buddhist temple in western Japan. He shaved his head, donned black robes and studied to become its leader. He passed the test, yet within a week was back at the Tokyo offices of ZMP Inc., overseeing his robotics company in the more typical garb of jeans and red Converse sneakers. As ZMP's founder and chief executive officer, he tries to sync millenniums-old teachings with efforts to make artificial intelligence part of everyday life. "The temple teaches you that if you shine, you'll shed light on those around you," Taniguchi, 52, said.

An Osaka-based startup founded by health care product group Fujimoto Holding Co. and toymaker Wiz Co. has released an upgraded version of a stuffed robot doll designed to be a conversation partner for elderly people. The new Unazuki Kabochan, released June 17, has been programmed with a greater variety of words and phrases, totaling around 450, allowing a greater scope of response to the user's words and actions, according to PIP & WiZ Co. The previous model could handle some 400 words and phrases, but sometimes failed to reply appropriately according to context. Selling for a suggested retail price of 27,000 at department stores and shops handling nursing care devices, the new Unazuki Kabochan can also sing 13 songs, eight more than the older unit, and the need to reset after it is switched off has been eliminated, the company said. The 28-cm, 680-gram doll is made to resemble a 3-year-old boy.

By early fall, a billboard in Tokyo will automatically identify the make and model of vehicles driving by it to display a targeted advertisement. "The ad could come up with'Hey you in the Mercedes, you could be driving this [instead],'" said Paul Turner, chief marketing officer with Cloudian, which is working with the Japanese company Dentsu on the project. A camera on the billboard will look hundreds of meters down the expressway to identify vehicles and present a corresponding ad for about five seconds. By targeting ads to specific types of vehicles, the companies should be able to charge a higher rate to advertisers. Highly-targeted ads are the norm while we browse the web and use apps, but such approaches have not largely entered the broader world yet.

In February this year, hackers managed to steal 81 million from the central bank of Bangladesh after exploiting vulnerabilities with a sophisticated malware. In January this year, press reports highlighted how highly destructive malware infected three regional power utility service providers in Ukraine, which led to a power failure. In June last year, CNN reported how hackers successfully managed to ground 1400 passengers, as Poland's national carrier was forced to cancel 20 flights due to an attack on its IT systems. In an age of connected machines, these incidents show how hackers can cause irreparable damage. Despite putting in place the best IT infrastructure, some of the biggest firms have got hacked, as vulnerabilities exist in every enterprise and hackers only need one loophole to sneak in an enterprise and steal data.

Genpact (NYSE: G), a global leader in digitally-powered business process management and services, announces that it has entered into a definitive agreement to acquire PNMsoft, a Gartner Magic Quadrant-rated dynamic workflow, case management and work optimization solutions provider based around Tel Aviv, Israel. PNMsoft complements and easily integrates pre-existing systems of records that typically host manual process work, and will act as a core component in Genpact's digital portfolio whose roadmap comprises close to 100 digital solution components ("digital assets"). Terms of the transaction were not disclosed. Closing is subject to satisfaction of certain customary conditions and expected in the third quarter. The transaction is not expected to be material to current year financial performance.

Contagions such as the spread of popular news stories, or infectious diseases, propagate in cascades over dynamic networks with unobservable topologies. However, "social signals" such as product purchase time, or blog entry timestamps are measurable, and implicitly depend on the underlying topology, making it possible to track it over time. Interestingly, network topologies often "jump" between discrete states that may account for sudden changes in the observed signals. The present paper advocates a switched dynamic structural equation model to capture the topology-dependent cascade evolution, as well as the discrete states driving the underlying topologies. Conditions under which the proposed switched model is identifiable are established. Leveraging the edge sparsity inherent to social networks, a recursive $\ell_1$-norm regularized least-squares estimator is put forth to jointly track the states and network topologies. An efficient first-order proximal-gradient algorithm is developed to solve the resulting optimization problem. Numerical experiments on both synthetic data and real cascades measured over the span of one year are conducted, and test results corroborate the efficacy of the advocated approach.

The input data features set for many data driven tasks is high-dimensional while the intrinsic dimension of the data is low. Data analysis methods aim to uncover the underlying low dimensional structure imposed by the low dimensional hidden parameters by utilizing distance metrics that consider the set of attributes as a single monolithic set. However, the transformation of the low dimensional phenomena into the measured high dimensional observations might distort the distance metric, This distortion can effect the desired estimated low dimensional geometric structure. In this paper, we suggest to utilize the redundancy in the attribute domain by partitioning the attributes into multiple subsets we call views. The proposed methods utilize the agreement also called consensus between different views to extract valuable geometric information that unifies multiple views about the intrinsic relationships among several different observations. This unification enhances the information that a single view or a simple concatenations of views provides.

June 27, Baltimore, MD - Youth Laboratories, the organizer of the first beauty contest judged by a panel of robots today announced the inclusion of AntiAgeist, an algorithm evaluating the difference between the chronological age of contest participants and the age predicted by a system of deep neural networks trained to predict human age. "We are very happy to have AntiAgeist on our jury of robot judges, since this is a rather novel idea of looking at beauty through the prism of how successfully the person is aging. We encourage teams from all over the world to submit algorithms and ideas on how machines can evaluate human beauty to the Beauty.AI contest. Best algorithms will get monetary prizes and will be promoted worldwide", said Anastasia Georgievskaya, general manager of Beauty.AI. Insilico Medicine specializes in drug discovery and biomarker development for a broad range of diseases with a mission to accelerate and improve lead generation and pre-clinical studies within biotechnology and pharmaceutical industries.

Mumbai: There is tremendous buzz around machine learning, broadly described as a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. However, despite an exponential increase in power, computers have typically proved incompetent at things that are really simple to human beings--like recognizing the dog in a picture containing a dog, or understanding speech. The trend, however, is changing. Consider'Deep Learning', which describes a collection of techniques that allow computational tasks that were previously thought impossible. Facebook Inc, for instance, uses it to identify faces, and when Google Inc recently announced that their algorithms could not only'see' a dog but also identify it as a Pomeranian, they heralded the maturity of Deep Learning techniques.