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Artificial Intelligence has been heralded as a game changer in the drive toward the intelligent enterprise. While AI and machine learning has been around for more than five decades, it's today's increasingly interconnected world and the continuing explosion of data that is driving an increase of applications powered by AI. AI promises to deliver exciting opportunities to IT as well as the business world, and many believe the reality is not far off. According to a recent report by Research and Markets, the AI market is estimated to grow from 419.7m ( 280m) in 2014 to 5.05bn ( 3.5bn) by 2020, at a CAGR of 53.65 per cent from 2015 to 2020. Major factors driving growth include diversified application areas of AI, improved productivity, and increased levels of customer satisfaction.

Bayesian Networks are a tool of new application to the question of risks, in particular for modeling operational risk. Its use for measuring operational risk in the financial sector has channeled large efforts in developing new methods that measure this type of risk which allow improving the internal gestation of the operational processes. Applying Bayesian Networks for modeling operational risk presents the opportunity to incorporate elements of qualitative analysis as well as the opinion of experts in the process of selecting interest variables, defining the structure of the model through its dependencies of causality, such as the specification of a priori distributions and conditional probabilities of each node. It has been found that Bayesian models that incorporate data as well as expert judgment (especially about causality) work better than any other method applicable in the field.

Tor is one of the world's most used anonymity networks, and offers a safe haven for internet users in oppressive regimes as well as criminals operating in cyberspace. The development of Tor was partly founded by the US government to help dissidents in countries with extreme internet censorship. The FBI however allegedly harassed a Tor developer after it started being used for criminal activities. Tor is one of the most used ways for users to hide their identity online. However, the Tor network can be compromised because of vulnerabilities in the network.

Back in December of 2015, Beijing city government issued its first red alert to signal that air pollutant levels were significant enough to cause risk to human health. As part of active red alert protocols, the city demands that automobile usage be reduced by 50%, and that heavy-load vehicles like garbage trucks and semis be banned from the road. This, in turn, slows local business, industry, and commerce to a near grinding halt. Flight cancellations are another common and undesirable side effect of these red alert transportation restrictions. Even worse still, however, are the ways in which this level of air pollution is affecting human health throughout Beijing and China at-large.

Tech companies are planning a burst of hiring over the next three years, according to a survey of technology company chief executive officers that was conducted by KPMG. Workforces at technology companies are expected to increase by at least 6 percent, the poll of CEOs found. High-tech firms also intend to bolster automation and machine learning in an array of functions, the KPMG survey of 138 tech CEOs determined. Technology executives also intend to find ways to meld additional workers with improved automation. "Tech CEOs see the benefits of digital labor augmenting workforce capabilities," said Gary Matuszak, global and U.S. chair of KPMG's Technology, Media and Telecommunications practice.

Big data in healthcare can now be measured in exabytes, and every day more data is being thrown into the mix in the form of patient-generated information, wearables and EHR systems. Traditional methods of analysis are no longer enough to handle, let alone take proper advantage of, the potential that healthcare data holds. This is where deep machine learning (or simply, "deep learning") comes in. However, its greatest power lies in its ability to extract value from data in ways that humans and traditional machine learning methods cannot. Deep machine learning has applications in a number of healthcare areas.

Jaguar Land Rover is working on a raft of technology that could enable its future production cars to drive autonomously off-road as well as on-road. The research project aims to make JLR's self-driving cars viable in a wide range of on- and off-road driving environments and conditions. To enable autonomous all-terrain capability, JLR is working on new sensing technologies to provide the high levels of artificial intelligence required for the car to plan the route it should take. New surface identification and 3D path sensing systems use camera, ultrasonic, radar and lidar sensors to give the car a 360-degree view of the world around it. JLR says the combined power of the sensors is so advanced that the car could determine road surface characteristics, down to the width of a tyre, even in rain and falling snow, to plan its route.

As SAILORS returns for the second summer, the new campers are giddy with excitement. After grabbing breakfast and getting to know one another, the girls situate themselves in a lecture room in the Gates Computer Science building at Stanford University. Professor Fei-Fei Li, director of the SAILORS program and the AI Lab as a whole, warmly welcomes the campers to the summer program, imparting the grounds on which the idea of an all-girls, two-week research-intensive program came about just two years ago. Though Professor Li acknowledges the recent talk of the possibility of AI becoming the "terminator next door" that some critics of the field fear, that was exactly what swayed her, along with co-director Olga Russakovsky, to feel the desperate need of bringing more females into the field of AI. Because, as Prof. Li puts it, when we have women who gravitate AI towards humanity–women who are compassionate, who care about AI safety–the potential benefits from the societal impact far outweigh the prospect of AI coming to dominate the world.

IBM's Watson has been turning out inventive culinary creations for quite some time. Now a London company wants to use AI to improve the beers they brew. A collaboration between a machine learning company and a creative firm has led to an AI application that even the least coherent of frat boys can get behind. IntelligentX co-founder Dr. Rob McInerney refers to what they're doing as "creativity structured by data." That combination, he says, allows them to improve their brews "generation after generation" -- something they hint at right on their labels.