In a dish of water in Cambridge, Massachusetts, a new kind of robot stirs, its tentacles twitching. Squashy and soft, this robot is different from its technological ancestors – Octobot runs without a power cable or rigid electronics, moving autonomously – if still clumsily – through the world. Soft robots have long been heralded as a new class of machine. But their tethers, and the electronics needed to control their movements, have held them back. Developed by Michael Wehner and colleagues at the Wyss Institute for Bioinspired Engineering, Harvard University, it's a big step towards fulfilling the potential of soft robots.

A pneumatic network, in red, is embedded within the octobot's entirely soft body and elastic arms, in blue. A pneumatic network, in red, is embedded within the octobot's entirely soft body and elastic arms, in blue. The squishy eight-legged robot described in the journal Nature is made entirely out of soft, flexible materials, runs on hydrogen peroxide, and looks like a 2-centimeter-tall baby octopus. It is a step forward for robotics, which has long relied on machines with hard skeletons (think The Terminator), or at least with rigid moving parts (like this other octopus-like guy designed by the Italian robot scientist Cecilia Laschi). In their paper, the authors say the systems behind their invention, which you can watch move in the video below, "may serve as a foundation for a new generation of completely soft, autonomous robots."

The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically achieved in a sub-second time frame, our model can be used as a high-throughput generator of reaction hypotheses for reaction discovery. Our innate ability to reason beyond established knowledge is one of the main driving forces of Science.

VCs are getting serious about space-related startups, and there are some truly exponential growth opportunities in the SpaceTech ecosystem. But the majority of money that went into SpaceTech last year was in just two deals -- a 1 billion fundraise for SpaceX and a 500 million raise for OneWeb. If you ignore those as outliers, SpaceTech funding in 2015 was only around 300 million. The segment of startups seeing the most VC attention is the earth observation (EO) segment. Companies building earth observation (EO) satellite constellations (basically, cameras put into orbit and photographing the Earth on a regular basis) pulled in more than half the SpaceTech funding from 2012 to 2015 and 72% in 2015.

By 2020, we will all have an Invisible Friend. Whether we call it Siri, Alexa, OK Google, or a chatbot, we are entering a world where an intelligence assistant recognizes our "intent." This could spawn a massive consumer behavior shift, as AI-influenced bots would mean far fewer Google searches by humans. This invisible friend would learn from its mistakes, maintain context, and continue to expand into new areas of expertise through judicious use of Knowledge Management (see below landscape). Although 2020 is our destination, now is a time of heightened activity among the companies that provide the elements of Intelligent Assistance.

During the 20th century, advances in fertilizers, irrigation, and mechanized farming technology helped make it possible to feed a dramatically growing world population. Now, advocates say, the next big advance in agricultural technology may come from the digital world, as modern computer vision, precision sensors, and machine-learning technology help farmers use last century's advances more efficiently and precisely to grow healthier and tastier food. "We're at the cusp of this next wave of innovation in agriculture, which we call digital agriculture," says Mike Stern, the president of The Climate Corporation. "It has to do with, over the past five to seven years, the farm really digitizing, not unlike how our society has changed in terms of the tools and types of things we can do." The Climate Corp., which was purchased by agriculture giant Monsanto for roughly 1 billion in 2013, is one of several companies working to build a digital analytics hub for farmers, merging images from satellites, drones, and cameras, as well as readings for everything from soil thermometers to tractors' on-board computers.

Soft robots aren't easy to make, since they require a completely different set of components from their rigid counterparts. It's even tougher to scale down the parts they typically use for locomotion. A team of researchers from the Faculty of Physics at the University of Warsaw, however, successfully created a 15-millimeter soft micromachine that only needs light to be able to move. The microrobot is made of Liquid Crystalline Elastomers (LCEs), smart materials that change shape when exposed to visible light. Under a light source, the machine's body contracts like a caterpillar and forms waves to propel it forward.

The use of data within an organisation to improve elements of the business such as the supply chain, improve decision making, and to make cost savings, is becoming more widely accepted as being vital. It is vital in respect to the business remaining competitive, vital to remaining relevant, and vital to the future of the business. One of the industries that has been looking significantly at the use of its data is the manufacturing industry, and stepping back one level to the steel industry. Magnitogorsk Iron and Steel Works (MMK), is the third largest steel company in Russia with a revenue of 9.3bn. Established in 1870, the company has taken to using machine learning technology from Yandex Data Factory to creative a competitive advantage that will see it being competitive for years to come.

A Florida-based company has won U.S. government permission to send a robotic lander to the moon next year. The move is the first time the United States has cleared a private space mission to fly beyond Earth's orbit. The Federal Aviation Administration's unprecedented go-ahead for the Moon Express mission also sets a legal and regulatory framework for a host of other commercial expeditions to the moon, asteroids and Mars. The Florida-based company Moon Express, which is partnering with Nasa, hopes to send scientific payloads to the Moon, in the hopes to eventually provide commercial services. Artist's impression of Moon Express lander on surface of the moon pictured The moon is a'treasure chest' of lucrative materials.

The self-assembling shape shifting killer robots from the Terminator films could be a step closer, thanks to the development of self-propelling liquid metals. A team of Australian researchers is laying the groundwork for T-1000s by creating the basis of soft electric circuits. Unlike modern circuitry found in electronic devices, which remain based on circuits with solid state components, future connections could be much more flexible and able to move and reconfigure as necessary. A team at RMIT University in Melbourne used non-toxic alloys of the metal gallium, which is liquid at close to room temperature. By adding droplets of the alloy galinstan to water and changing the pH, they were able to make the drops move about freely.