The calculation of minimum energy paths for transitions such as atomic and/or spin re-arrangements is an important task in many contexts and can often be used to determine the mechanism and rate of transitions. An important challenge is to reduce the computational effort in such calculations, especially when ab initio or electron density functional calculations are used to evaluate the energy since they can require large computational effort. Gaussian process regression is used here to reduce significantly the number of energy evaluations needed to find minimum energy paths of atomic rearrangements. By using results of previous calculations to construct an approximate energy surface and then converge to the minimum energy path on that surface in each Gaussian process iteration, the number of energy evaluations is reduced significantly as compared with regular nudged elastic band calculations. For a test problem involving rearrangements of a heptamer island on a crystal surface, the number of energy evaluations is reduced to less than a fifth. The scaling of the computational effort with the number of degrees of freedom as well as various possible further improvements to this approach are discussed.

The optimization of algorithm (hyper-)parameters is crucial for achieving peak performance across a wide range of domains, ranging from deep neural networks to solvers for hard combinatorial problems. The resulting algorithm configuration (AC) problem has attracted much attention from the machine learning community. However, the proper evaluation of new AC procedures is hindered by two key hurdles. First, AC benchmarks are hard to set up. Second and even more significantly, they are computationally expensive: a single run of an AC procedure involves many costly runs of the target algorithm whose performance is to be optimized in a given AC benchmark scenario. One common workaround is to optimize cheap-to-evaluate artificial benchmark functions (e.g., Branin) instead of actual algorithms; however, these have different properties than realistic AC problems. Here, we propose an alternative benchmarking approach that is similarly cheap to evaluate but much closer to the original AC problem: replacing expensive benchmarks by surrogate benchmarks constructed from AC benchmarks. These surrogate benchmarks approximate the response surface corresponding to true target algorithm performance using a regression model, and the original and surrogate benchmark share the same (hyper-)parameter space. In our experiments, we construct and evaluate surrogate benchmarks for hyperparameter optimization as well as for AC problems that involve performance optimization of solvers for hard combinatorial problems, drawing training data from the runs of existing AC procedures. We show that our surrogate benchmarks capture overall important characteristics of the AC scenarios, such as high- and low-performing regions, from which they were derived, while being much easier to use and orders of magnitude cheaper to evaluate.

However, our reason to come to Engadin was not to snowboard or ski, but to work on innovative solutions in order to maximise the region's potential. Ten selected startups from all over Europe came to St. Moritz for three days to develop new ideas, create prototypes and, of course, connect with great people from different companies. We were lucky to be one of the chosen startups. Our team was the only one that decided to work on two topics, "chatbots" & "data analytics," because we felt that both were necessary to create the best customer experience. The first evening was a get-together -- informal dinner and fun activities where tech founders, investors, innovation executives, and tourism experts got to know each other.

Need a teacher, airport guide, care taker, and customs control officer all in one? Standing at just under 3 feet tall with big cartoon eyes and flipper arms, Sanbot looks more helpless than helpful, but don't let that cute appearance fool you. Sanbot is packed with features to help "her" get the job done. Sanbot has 14 of them scattered throughout its three foot frame. Many of these are touch sensitive, allowing the robotic lady to respond with human-like emotion to a particular tap.

People have been losing jobs to robots since the 1990's, a new report has revealed. When one or more robots was introduced into the workforce between 1990 and 2007, it led to the elimination of an average of six jobs. During those years, robots accounted for the loss of about 670,000 manufacturing jobs, and this is expected to rise in the coming years as robots continue to take over tasks previously performed by people. The effects of automation on employment for men are about 1.5-2 times large than those for women The report, published by the National Bureau of Economic Research, estimated that one more robot per thousand workers reduces wages by 0.25-0.5 per cent. Between 1993 and 2007, the authors of the report wrote that'the stock of robots in the United States and Western Europe increased fourfold'.

Pizza company Domino's teased a driverless delivery robot back in 2015, and now it will be a reality for some customers. Domino's is using a fleet of autonomous robots built by Starship Technologies to deliver pizza in European cities, Starship announced Wednesday. The robots, which are different from the previously teased vehicle, will deliver pizzas within a one-mile radius around a Domino's locations in selected cities in the Netherlands and Germany. Domino's Group CEO Don Meij said the robot delivery units will "complement" the company's current delivery methods, such as cars, scooters and e-bikes. He added that the partnership between the pizza company and Starship makes regular robot deliveries one step closer to reality.

Starship Technologies, the London-based company that has created six-wheeled self-driving delivery robots, will begin taking customers Domino's pizzas in Germany and the Netherlands.

"We call them'flourishes'," says Aldo Faisal. "Kevin has this flourish where, because he can rotate his wrist 360-degrees either way, when he reaches for or passes you stuff he will add this flourish just for the fun of it. There's no need for him to do it, but he does it anyway. It's like if you pick up your teacup and you stretch out your pinkie finger… He doesn't think about it: he just does it." Faisal, senior lecturer in Neurotechnology at Imperial College London, is talking to WIRED about one of his'Pilots': the term given to disabled athletes taking part in the 2016 Cybathlon in Switzerland.

Apple is reportedly still interested in its self-driving car venture, Project Titan, a recent report from a Swiss local site Inside IT via Apple Insider suggests. The company is said to quietly operating a research lab in Switzerland and has hired computer visions and robotics researchers, the site said. The facility could be linked to Apple's autonomous car project. At least 10 doctoral and postdoctoral students from ETH Zurich University have left the school for the research facility, the report said. "The specialists from the laboratories for computer vision and robotics are particularly in demand," Inside IT reported.

Samsung officially revealed the new Galaxy S8 and S8 Plus here in New York, and it seems safe to say that we got what we expected. The lack of a home button; the new AI assistant; the near bezel-less, curved screens; the rear-mounted fingerprint sensors -- all the leaks were true. What ultimately matters more than the lack of surprises are ambition and keen execution, and Samsung clearly embraced both when building the S8s. It's a good thing too: After the Galaxy Note 7's rise and fiery fall, Samsung needed to prove that it could craft some flawless smartphones. Well, I'm not sure about flawless, but the S8 and S8 Plus are both gorgeous and full-featured -- for now, the good certainly seems to outweigh the bad.