This example of programmable architecture uses lightweight materials and drones to help it adapt to environmental changes. Digital fabrication and automation is changing the way we build, allowing for cutting-edge concepts to take form through computer-aided design tools and integrating robotics into building techniques. Three graduate students over at University of Stuttgart's Institute for Computational Design and Construction (ICD) and Institute of Building Structures and Structural Design (ITKE) recently unveiled a modular architectural canopy that can be reconfigured in real-time, using drones. Dubbed Cyber Physical Macro Material, the 2.5-metre (8.2-foot) high canopy is designed as a "new dynamic (and intelligent) agile architecture for public spaces," which can respond to weather conditions. Built with lightweight carbon fibre filament, magnets and a variety of sensors and processors, the canopy demonstrates the possibility of'live' construction processes, facilitated by unmanned aerial vehicles (UAVs).

They then synthesized and tested one of the compounds predicted computationally -- sodium-barium-borate -- and determined it offers 95 percent efficiency and outstanding thermal stability. Jakoah Brgoch, assistant professor of chemistry, and members of his lab describe the work a paper published Oct. 22 in Nature Communications. The researchers used machine learning to quickly scan huge numbers of compounds for key attributes, including Debye temperature and chemical compatibility. Brgoch previously demonstrated that Debye temperature is correlated with efficiency. LED, or light-emitting diode, based bulbs work by using small amounts of rare earth elements, usually europium or cerium, substituted within a ceramic or oxide host -- the interaction between the two materials determines the performance.

A few years ago I saw this headline news flashing all over the internet. Our dealers are missing up to $18 billion in easy sales. The Chairman and CEO of Caterpillar suggested that the company and its dealers were losing $9 - 18 billion in easy sales revenue as their sales, both internal and dealer networks, weren't monetising the real value of data. They are not tapping into the wealth of real-time customer data now at their fingertips; they are not communicating with each other; and they are not providing customers across the globe with a consistent experience when it comes to everything from e-commerce to parts and services pricing. Long story short, the whole idea was to convert the company's mentality from dumb iron sales to data-driven, machine learning-driven sales.

Researchers from the University of Houston have devised a new machine learning algorithm that is efficient enough to run on a personal computer and predict the properties of more than 100,000 compounds in search of those most likely to be efficient phosphors for LED lighting. Jakoah Brgoch, assistant professor of chemistry, and members of his lab describe the work a paper published Oct. 22 in Nature Communications. The researchers used machine learning to quickly scan huge numbers of compounds for key attributes, including Debye temperature and chemical compatibility. Brgoch previously demonstrated that Debye temperature is correlated with efficiency. LED, or light-emitting diode, based bulbs work by using small amounts of rare earth elements, usually europium or cerium, substituted within a ceramic or oxide host--the interaction between the two materials determines the performance.

The UCR Time Series Archive - introduced in 2002, has become an important resource in the time series data mining community, with at least one thousand published papers making use of at least one dataset from the archive. The original incarnation of the archive had sixteen datasets but since that time, it has gone through periodic expansions. The last expansion took place in the summer of 2015 when the archive grew from 45 datasets to 85 datasets. This paper introduces and will focus on the new data expansion from 85 to 128 datasets. Beyond expanding this valuable resource, this paper offers pragmatic advice to anyone who may wish to evaluate a new algorithm on the archive. Finally, this paper makes a novel and yet actionable claim: of the hundreds of papers that show an improvement over the standard baseline (1-Nearest Neighbor classification), a large fraction may be misattributing the reasons for their improvement. Moreover, they may have been able to achieve the same improvement with a much simpler modification, requiring just a single line of code.

Technology giant Huawei aims to help train one million artificial intelligence (AI) talents in the next three years to boost the fast-expanding sector. Huawei will provide free online training, organise boot camps and collaborate with industry players. It will also set up a one billion yuan (S$199 million) fund for universities and research institutes to support AI talent development. Mr Zheng Yelai, Huawei's vice-president and president of its cloud business unit, announced this yesterday, the last day of the Huawei Connect Conference in Shanghai. The move is in line with China's push to become a global AI powerhouse in the next decade.

Computers used to take up entire rooms. Today, a two-pound laptop can slide effortlessly into a backpack. But that wouldn't have been possible without the creation of new, smaller processors -- which are only possible with the innovation of new materials. But how do materials scientists actually invent new materials? Through experimentation, explains Sanket Deshmukh, an assistant professor in the chemical engineering department whose team's recently published computational research might vastly improve the efficiency and costs savings of the material design process.

Well-known Belfast startup Axial3D produces 3D prints of your body parts. This isn't to satisfy the narcissistic social media types – it has important surgical implications. This previous TechWatch article describes the company's process. Now, Axial3D is developing new AI techniques to make instantaneous the transition from 2D images to 3D prints. How are they doing that?

My sandwich looked like something out of a restaurant commercial: glossy yellow cheese oozing between two golden-brown slices of toast. The first bite should have been rich, gooey and decadent. I stalked back to the kitchen, pulled open the fridge door, and snatched the culprit. Printed on the back of the plastic package--Mexican Style Blend Finely Shredded Cheese, left by a visiting friend--was an ingredient list longer than just "cheese." Food additives are a fact of modern life--they improve shelf-life, flavor, texture, consistency and color.

Kubernetes is becoming synonymous with cloud-native computing. As an open-source platform, it enables development, deployment, orchestration and management of containerized microservices across multicloud ecosystems. Kubernetes is the key to cloud-native microservices that are platform agnostic, dynamically managed, loosely coupled, distributed, isolated, efficient, and scalable. The maturation of Kubernetes continues to deepen as it leverages containers, orchestrations, service meshes, immutable infrastructure, and declarative APIs. One clear indicator of Kubernetes' maturation is the rich ecosystem of other open-source projects that have grown up around it.