This smooth and flexible robot, modeled after an octopus, glows under black light. It took two years to perfect but only a few dollars' worth of materials to produce. An "octobot" less than three inches wide is changing the robotics landscape. The octobot is the world's first completely soft, autonomous, and untethered robot. It is free of wires, batteries, and any hard material--like its namesake, the octopus, which has no internal skeleton.

This question originally appeared on Quora. This means if you were to remove everything you can see and interact with in the visible universe (people, food, home appliances, planets, stars, galaxies, nebulae, etc.), there would still be 95% of the universe remaining! The result is that there is more dark matter and dark energy in the room you are currently in than normal matter. It is percolating through your body as you read this answer! The general rule is that dark matter holds galaxies together and dark energy drives the expansion of the universe. It is the ultimate tug of war. At the beginning of the universe, dark matter was much more powerful than dark energy, which is what allowed early galaxies to form. But dark energy has now taken over and is causing distant galaxies to recede from us at a rate faster than the speed of light. As you may know, no object with mass can exceed the speed of light, however there is no limit on the speed at which the spacetime medium (which ...

Integrated Computational Materials Engineering (ICME) aims to accelerate optimal design of complex material systems by integrating material science and design automation. For tractable ICME, it is required that (1) a structural feature space be identified to allow reconstruction of new designs, and (2) the reconstruction process be property-preserving. The majority of existing structural presentation schemes rely on the designer's understanding of specific material systems to identify geometric and statistical features, which could be biased and insufficient for reconstructing physically meaningful microstructures of complex material systems. In this paper, we develop a feature learning mechanism based on convolutional deep belief network to automate a two-way conversion between microstructures and their lower-dimensional feature representations, and to achieves a 1000-fold dimension reduction from the microstructure space. The proposed model is applied to a wide spectrum of heterogeneous material systems with distinct microstructural features including Ti-6Al-4V alloy, Pb63-Sn37 alloy, Fontainebleau sandstone, and Spherical colloids, to produce material reconstructions that are close to the original samples with respect to 2-point correlation functions and mean critical fracture strength. This capability is not achieved by existing synthesis methods that rely on the Markovian assumption of material microstructures.

Even a simple chemical reaction can be surprisingly complicated. That's especially true for reactions involving catalysts, which speed up the chemistry that makes fuel, fertilizer and other industrial goods. In theory, a catalytic reaction may follow thousands of possible paths, and it can take years to identify which one it actually takes so scientists can tweak it and make it more efficient. Now researchers at the Department of Energy's SLAC National Accelerator Laboratory and Stanford University have taken a big step toward cutting through this thicket of possibilities. They used machine learning – a form of artificial intelligence – to prune away the least likely reaction paths, so they can concentrate their analysis on the few that remain and save a lot of time and effort.

Steel production is an area that has been studied for decades, and as such the industry has remained very conservative. Despite the big data revolution beginning in the early 2000s, "old-school" industries like steel-making have largely shunned any form of data-driven applications. Fortunately, things change, and here's an example of how data analytics technologies, born within the internet industry, can be applied to an offline practice like turning pig iron into steel. When we began work with Magnitogorsk Iron and Steel Works (MMK), one of the world's largest steel producers and a leading steel company in Russia, a lot of time was spent looking for a challenge that if solved, could (a) positively impact business revenues, and (b) be completed in reasonable time.The challenge that was eventually uncovered and able to meet these criteria, is one well-known to all metallurgists: how much of each ferroalloy to add during steel-making process in order to ensure the required chemistry of the steel at the lowest possible cost. This chemistry is dictated by the international standards for steel – a list of required ranges for the amounts of each element in the final mix.

Planetary Resources, a company hoping to make asteroid mining into a trillion dollar industry, earlier this year unveiled the world's first 3D printed object made from bits of an asteroid. Just a few years ago, most 3D printing was only used for building prototypes, which would then go on to be manufactured via conventional processes. But it's now increasingly being used for manufacturing in its own right. Nearly two years ago, NASA even sent a 3D printer to the International Space Station with the goal of testing how the technology works in micro-gravity. While the printer resembles a Star Trek replicator, it's not quite that sophisticated yet; the objects it can print are small prototypes for testing.

Generally, the term "aerial robot" is synonymous with "drone," but there are lots of other ways for robots to avoid spending time on the ground. One of the most creative that we've seen recently comes from Georgia Tech Professor Jonathan Rogers, who has been working on a sloth-inspired aerial robot named Tarzan. The machine is designed to swing around on overhead wires strung above fields to monitor growing crops. And one day, it may swing around electrical wires in cities, too. Tarzan is built with carbon fiber arms, reinforced with aluminum.

The nineteenth century marked the acceleration and wide adoption of industrial processes. In the twentieth century, technology moved from the laboratory and research institute to the home. We are now at the cusp of a new technological shift of equal significance: the Robotics Revolution. But what is the Robotics Revolution and what will it actually deliver? A "robot" is often defined as a machine that can carry out a complex series of actions automatically, especially one programmable by a computer.

David Mitchell pulls into the parking lot of the Desert Research Institute, an environmental science outpost of the University of Nevada, perched in the dry red hills above Reno. On this morning, wispy cirrus clouds draw long lines above the range. Mitchell, a lanky, soft-spoken atmospheric physicist, believes these frigid clouds in the upper troposphere may offer one of our best fallback plans for combating climate change. But Mitchell, an associate research professor at the institute, thinks there might be a way to counteract the effects of these clouds. It would work like this: Fleets of large drones would crisscross the upper latitudes of the globe during winter months, sprinkling the skies with tons of extremely fine dust-like materials every year. If Mitchell is right, this would produce larger ice crystals than normal, creating thinner cirrus clouds that dissipate faster.

In the 2012 sci-fi film Prometheus, scientists release small drones into a mysterious tunnel complex to create a detailed 3D map of the caverns in minutes. Australian researchers plan to use a similar approach to explore parts of old mines that are unsafe to visit. The drones, which are controlled by a pilot, will be able to carry out safety checks by monitoring the build-up of water and checking the extent of roof collapses, and search for valuable mineral deposits that may have been missed. They are being developed by Craig Lindley and his colleagues at the Commonwealth Scientific and Industrial Research Organisation, Australia's government research agency. The researchers' model is based on a commercial quadcopter.