Robots are probably the first thing you think of when asked to imagine AI applied to industrials and manufacturing. Indeed many innovative companies like Rodney Brooks' Rethink Robotics have developed friendly-looking robot factory workers who hustle alongside their human colleagues. Industrial robots have historically been designed to perform specific niche tasks, but modern-day robots can be taught new tasks and make real-time decisions. As sexy and shiny as robots are, the vast majority of the value of AI in manufacturing lies in transforming data from sensors and routine hardware into intelligent predictions for better and faster decision-making. By 2020, Cisco predicts the number will surpass 50 billion.

Every person on Earth got the equivalent of an extra x-ray from the Fukushima nuclear disaster, a new study claims. Researchers have carried out the first global survey of radiation exposure caused by the meltdown of three nuclear reactors at the Fukushima-Daiichi nuclear plant in Japan after a tsunami struck in 2011. They concluded that people need not panic about the dosage. Every person on Earth got the equivalent of an extra x-ray from the Fukushima nuclear disaster, a new study claims. 'We don't need to worry,' Nikolaos Evangeliou at the Norwegian Institute for Air Research, whose team conducted the tests, told the annual meeting of the European Geosciences Union in Vienna, Austria, last month, according to New Scientist.

The Internet of Things (IoT) is poised to fundamentally change the way a wide range of industries approach the procurement, processing, and distribution of raw materials and finished products. New efficiencies based on the introduction of intelligent sensors, mission-critical communications, automation, and robotics will optimize industries ranging from mining and shipping to manufacturing verticals including electronics, automotive and petrochemical products. This emerging megatrend is alternatively called the Fourth Industrial Revolution and Industry 4.0, although these aren't interchangeable terms. Let's take a look at both. The First Industrial Revolution, which started in Britain around 1760 and ran until between 1820 and 1840, saw the mechanization of the textile industry via a transition from hand tools to machine tools.

As manufacturing processes become increasingly automated, so should tool condition monitoring (TCM) as it is impractical to have human workers monitor the state of the tools continuously. Tool condition is crucial to ensure the good quality of products: Worn tools affect not only the surface quality but also the dimensional accuracy, which means higher reject rate of the products. Therefore, there is an urgent need to identify tool failures before it occurs on the fly. While various versions of intelligent tool condition monitoring have been proposed, most of them suffer from a cognitive nature of traditional machine learning algorithms. They focus on the how to learn process without paying attention to other two crucial issues: what to learn, and when to learn. The what to learn and the when to learn provide self regulating mechanisms to select the training samples and to determine time instants to train a model. A novel tool condition monitoring approach based on a psychologically plausible concept, namely the metacognitive scaffolding theory, is proposed and built upon a recently published algorithm, recurrent classifier (rClass). The learning process consists of three phases: what to learn, how to learn, when to learn and makes use of a generalized recurrent network structure as a cognitive component. Experimental studies with real-world manufacturing data streams were conducted where rClass demonstrated the highest accuracy while retaining the lowest complexity over its counterparts.

In the past couple of months we've spent a lot of time meeting with different experts in the Oil & Gas industry such as with geologists, production managers, drillers, manufacturers etc. Every conversation we had about AI we have been asked the question: Is AI going to replace humans in Oil & Gas? This question led us to research this issue and to have a better understanding of where this industry is going. Our conclusion was that the collaboration between humans and AI is the right answer. Both have some strengths and weaknesses which are opposite from each other, so combining domain experts and AI could lead the industry to a new age.

A wildfire broke out over the weekend in an uninhabited portion of Japan's Fukushima prefecture, sparking concerns that the blaze might spread airborne radiation. The fire started on Mount Juman in Namie, where radiation has remained high enough since the 2011 disaster for officials to continue declaring it a "difficult-to-return zone." Eight helicopters from Fukushima, Miyagi and Gunma prefectures were dispatched to the site, Japanese newspaper the Mainichi reported Monday. When those helicopters couldn't stop the flames, local officials called in the Ground Self-Defense Force, a branch of the Japanese military, to help. The fire was likely started by lightning in the uninhabited region, the Mainichi reported.

"A Conversation with Elon Musk" at the World Government Summit 2017 in Dubai While in Dubai for the official launch of Tesla in the UAE, Elon Musk attended the World Government Summit 2017 to unpack his current focus areas for local leaders. Musk shared his usual themes of sustainability, electrified transport, dying on Mars and more recently, warnings about runaway artificial intelligence, while in Dubai. In what felt like the awkward clash of a teenage reverie and middle eastern culture, Elon dove into the possibility of life being a virtual experience and not a physical experience, noting the almost indiscernible difference between graphics in modern video games and our perception of the physical world. These ponderings naturally dovetailed into warnings about the possibility of negative outcomes for artificial intelligence which is one of Elon's new focus areas as he looks to life beyond Tesla. Elon talked about he is looking to unlock the full capacity of humans with cyborg plugins…and how we are already using technology to do this which an obvious hint at his interest in a neural lace.

ABB and IBM are bringing together ABB's industry leading digital offering, ABB AbilityTM, with IBM Watson Internet of Things cognitive capabilities to unlock new value for customers in utilities, industry, transport and infrastructure. Get started with Watson IoT: www.ibm.com/iot Continuing more than a 125-year history of innovation, ABB today is writing the future of industrial digitalization and driving the Energy and Fourth Industrial Revolutions. ABB operates in more than 100 countries with about 132,000 employees.

What looks like a tiny mechanical ostrich chasing after a car is actually a significant leap forward for robot-kind. The clever and simple two-legged robot, known as the Planar Elliptical Runner, was developed at the Institute for Human and Machine Cognition in Ocala, Florida, to explore how mechanical design can be used to enable sophisticated legged locomotion. A video produced by the researchers shows the robot being tested in a number of situations, including on a treadmill and running behind and alongside a car with a helping hand from an engineer. In contrast to many other legged robots, this one doesn't use sensors and a computer to help balance itself. Instead, its mechanical design provides dynamic stability as it runs.

China has overtaken the United States to become the world leader in deep learning research, a branch of artificial intelligence (AI) inspired by the human brain. Deep learning algorithms are modeled on biological neural networks and enable machines to learn and mimic human-like responses. Think: smartphone assistants answering your questions, or Amazon recommending products based on your search and purchasing history.