The World Economic Forum has put together a list of the top 10 emerging technologies that will change our lives. The list includes nanosensors that will circulate through the human body, a battery that will be able to power an entire town and socially aware artificial intelligence that will track our finances and health. These are not far-flung visions, according to the forum. They are technologies that are on the cusp of having a meaningful impact. "Horizon scanning for emerging technologies is crucial to staying abreast of developments that can radically transform our world, enabling timely expert analysis in preparation for these disruptors," said Bernard Meyerson, chairman of the World Economic Forum council that compiled the list of the top 10 emerging technologies in 2016.

Today on In Case You Missed It: The chemical makeup of pig manure is so similar to petroleum that it's being tested as a more bio-friendly way to make asphalt roads, while the leftover bits can be used as fertilizer. Since pigs already produce 43 billion gallons of manure each year, re-using some for road construction might be the smartest thing we've done with bioengineering yet. You can find our diabetes story from Cambridge here, the first banking chatbot from Kasisto here, and the selfie drone that's going to be everywhere, here.

To some people, electricity is like air: There for the taking. For others, circumventing paying a utility bill is a just cause, sticking it to "Big Energy" for their perceived transgressions against customers. In either case, not paying for energy is considered fraud and a crime. In some states, energy fraud is a felony worthy of hard time and steep penalties. The numbers tell the story.

Genpact (NYSE: G), a global leader in digitally-powered business process management and services, today launched its Neural Intelligence Platform that harnesses the power of artificial intelligence technologies, and brings middle and back office processing to the same level of digital automation as the front office to drive seamless customer journeys. Using a cognitive system powered by natural language processing, machine and deep learning techniques, the platform provides a versatile artificial intelligence-based capability that digitizes many business process solutions, including omni-channel management, contact center, account payable query management, and financial and accounting automation. The platform is the result of more than a decade of research and development in high performance business processing practices, recently crystallized into digital solutions through an aggressive build out of advanced technologies including robotic process automation, natural language processing, and machine learning. The platform also leverages Genpact's unique Lean DigitalSM approach that harnesses the combined power of process-centric technologies, design thinking, and deep domain expertise.

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.

It's been said that the true harbinger of scientific discovery is not "Eureka!" but "Huh… that's funny…." That certainly proved to be the case for Sebastian Bianchi: a simple cup of tea led him to some intriguing, counter-intuitive insights into the surface tension of water. Preparing mate involves pouring hot water over mate leaves packed into a cup and letting them steep. Generally, things tend to flow downstream, yet he found a few mate leaves inexplicably ended up back in the kettle. Somehow, they had traveled upstream.

Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, discussed how research has demonstrated the value of Machine Learning in delivering next generation analytics to improve safety, performance, and reliability in today's modern wind turbines. Speaker Bio Stuart Gillen is the Director of Business Development at SparkCognition. In this role, he is responsible for driving business engagements, partner development, marketing activities, and go-to market strategy.

When you think of artificial intelligence, the first image that likely comes to mind is one of sentient robots that walk, talk and emote like humans. But a different kind of AI is becoming prevalent in nearly all of the sciences. It's known as machine learning, and it revolves around enlisting computers in the task of sorting through the massive amounts of data that modern technology has allowed us to generate (a.k.a. One place machine learning is turning out to be the most beneficial is in the environmental sciences, which have generated huge amounts of information from monitoring Earth's various systems -- underground aquifers, the warming climate or animal migration, for example. A slew of projects have been popping up in this relatively new field, computational sustainability, that combine data gathered about the environment with a computer's ability to discover trends and make predictions about the future of our planet.

It took millennia for Humanity to advance from the Stone Age to the Industrial Revolution. The pace of Human development continues to rapidly accelerate. The next Revolution is already overtaking society before many are ready for- or even aware of it. Both diametrically opposed predictions curiously are based on the premise that Humans will blithely give up control to either benevolent or diabolical machine'overlords'. There are arguments for both extremes, and both sides raise enough valid questions provoke meaningful dialogue on AI ethics and control. While History reminds us that extreme people and ideas often provide valid counterweight to over-enthusiasm and even zealotry from opposing people and views, they usually tend to be mere lane markers for History's true road.

C3 IoT will provide ENGIE the necessary power, scalability and flexibility to apply machine-learning and advanced real time analytics to very large petabyte-scale data sets. Chris Preimesberger is Editor of Features and Analysis at eWEEK.