It was just about a month ago that Christopher Trout put up a post on Engadget introducing himself as our new editor-in-chief. Since then, we've been busy drilling down into the areas we cover best: consumer electronics ("gear"), gaming and entertainment, with the odd story on politics, culture or science, when it makes sense. So often, consumer tech is about the near future: iterative updates and products you can buy now or very soon. With Tomorrow, we turn our attention to the unknown. Tomorrow shines a light on the products, technologies ideas and people that will drastically change the way we live.

Last week taurob, together with research partner TU Darmstadt, was announced the winner of the ARGOS Challenge, powered by Oil & Gas giant Total S.A. In a three-year competition, five international teams competed to develop a robot for routine-, inspection- and emergency operations on oil & gas sites. Frequently, gas leaks on oil drilling rigs can cause an increased risk to safety and the environment. The acronym ARGOS stands for Autonomous Robot for Gas and Oil Sites, which suggests that the robot independently performs assigned tasks. If necessary, an operator can intervene at any time via a satellite-based connection from land and take control of the robot.

The following address was given by Cylance Chief Security & Trust Officer Malcolm Harkins to the United States Senate in March 2017. We believe it's important enough to share with the public and start a dialogue so that we can band together to find the solutions we so clearly need in order to secure our vastly-changing future. The march of technology can be viewed as a succession of major waves, each lasting roughly 100 years (Rifkin 2013). Each wave has brought transformative benefits to society, but also significant challenges. The first wave, starting in the 1760s, included steam power, railways, and early factories, as well as mass education and printing.

This paper proposes three different distributed event-triggered control algorithms to achieve leader-follower consensus for a network of Euler-Lagrange agents. We firstly propose two model-independent algorithms for a subclass of Euler-Lagrange agents without the vector of gravitational potential forces. By model-independent, we mean that each agent can execute its algorithm with no knowledge of the agent self-dynamics. A variable-gain algorithm is employed when the sensing graph is undirected; algorithm parameters are selected in a fully distributed manner with much greater flexibility compared to all previous work concerning event-triggered consensus problems. When the sensing graph is directed, a constant-gain algorithm is employed. The control gains must be centrally designed to exceed several lower bounding inequalities which require limited knowledge of bounds on the matrices describing the agent dynamics, bounds on network topology information and bounds on the initial conditions. When the Euler-Lagrange agents have dynamics which include the vector of gravitational potential forces, an adaptive algorithm is proposed which requires more information about the agent dynamics but can estimate uncertain agent parameters. For each algorithm, a trigger function is proposed to govern the event update times. At each event, the controller is updated, which ensures that the control input is piecewise constant and saves energy resources. We analyse each controllers and trigger function and exclude Zeno behaviour. Extensive simulations show 1) the advantages of our proposed trigger function as compared to those in existing literature, and 2) the effectiveness of our proposed controllers.

Early detection of cancer: Developing NLP classifiers to analyze biomedical literature microRNAs are bio-markers, which may indicate cancer and other diseases even at early stage. Together, we developed a pipeline and an NLP classifier to detect relations between genes and micro-RNAs in medical research documents. The generalized code and leanings are open sourced and shared on Github. Sound and vision: Visual anomalies from audio data using deep learning We walk you through an effort by Sierra Systems with help from Microsoft and the Microsoft Cognitive Toolkit to detect and classify oil pipeline leaks, using audio data from a sensor ball deployed by Pure Technologies. We convert this audio data into images and use state-of-the-art Deep Learning techniques in the realm of image recognition to find'visual' anomalies and tell leaks from everyday events.

While the oil and gas industry has had its share of ups and downs over the past decade, many financial institutions are banking on a very slow growth of oil prices in 2017. Though some believe that the efficiency gains that the oil industry can capture are quickly coming to an end, this sentiment is only capturing hard technology specifically related to oil and gas. To help bring the O&G industry to the 21st century, technology from other industries needs to be incorporated, using many hard-earned years of expertise and different lines of thinking. Oilprice previously mentioned incorporating food industry technology to increase safety standards when fracking, but incorporating technology from the IT industry is something that the O&G industry as a whole can benefit from. Whether its neural networks, machine learning, fuzzy logic, case-based reasoning or expert systems, AI has the potential to transform the industry.

The Mirai is Toyota's car of the future. It runs on hydrogen fuel cells, gets 312 miles on a full tank and only emits water vapor. So, to target tech and science enthusiasts, the brand is running thousands of ads with messaging crafted based on their interests. The campaign was written by IBM's supercomputer, Watson. After spending two to three months training the AI to piece together coherent sentences and phrases, Saatchi LA began rolling out a campaign last week on Facebook called "Thousands of Ways to Say Yes" that pitches the car through short video clips.

The Jevons Paradox suggests that when technological advances increase efficiency of a resource, it results in an overall increase in consumption. Writing on the increased use of coal as a result of technological improvements, 19th-century economist William Stanley Jevons found that these improvements led to the development of new ways to utilize coal. In his session at 19th Cloud Expo, Mark Thiele, Chief Strategy Officer for Apcera, compared the Jevons Paradox to modern-day enterprise IT, examining how the Internet and the cloud has allowed for the democratization of IT, resulting in an increased demand for the cloud and the drive to develop new ways to utilize it. Speaker Bio Mark Thiele's successful career in IT spans 25 years and has focused on both operating roles and on driving cloud adoption across enterprises of all sizes. He has deep industry experience and extensive knowledge of the requirements of policy-driven cloud computing and drives cross-functional strategic initiatives as Chief Strategy Officer for Apcera.

You have to jump before you can fly. A species of tiny parrot saves energy by hopping from branch to branch when foraging – a skill that may have helped bird ancestors to first get off the ground. These small birds hop between branches up to 30 times a minute, gaining propulsion from their legs and adding a few wingbeats to extend their range. A new study shows they do this in ways that minimise energy requirements, and suggests bird-like dinosaurs might have benefited from the technique too. To examine the biomechanics of these short flights, the Pacific parrotlets were trained to fly between perches for a food reward.

That's the thin line Tropico dev Haemimont Games is aiming for with its newly announced city builder Surviving Mars. It's a game about surviving on Mars, if you can believe it. This is no SimCity or Cities: Skylines. Nor is it Tropico, with its comical dictator and his near-infinite powers. The consequences of failure are so much greater here.