Olli will be exclusive to DC these next few months, but Miami and Las Vegas will get their own in late 2016. Local Motors is also in talks to test the bus in cities outside the US, including Berlin, Copenhagen and Canberra. It's unclear if anyone can get the chance to ride one, since these are merely trial runs, but you can ask local authorities if the EV makes its way to your city. If and when the time comes that driverless public vehicles can legally shuttle passengers, you'll be able to summon an Olli through an app, just like Uber. And if Local Motors' plans pan out, a lot of people around the globe will be using that app: Company co-founder John Rogers envisions building hundreds of micro-factories all over the world that can 3D print an Olli within 10 hours and assemble it one.

The importance of algorithms in our lives today cannot be overstated. They are used virtually everywhere, from financial institutions to dating sites. But some algorithms shape and control our world more than others -- and these ten are the most significant. Just a quick refresher before we get started. Though there's no formal definition, computer scientists describe algorithms as a set of rules that define a sequence of operations.

It has been noticed that some external CVIs exhibit a preferential bias towards a larger or smaller number of clusters which is monotonic (directly or inversely) in the number of clusters in candidate partitions. This type of bias is caused by the functional form of the CVI model. For example, the popular Rand index (RI) exhibits a monotone increasing (NCinc) bias, while the Jaccard Index (JI) index suffers from a monotone decreasing (NCdec) bias. This type of bias has been previously recognized in the literature. In this work, we identify a new type of bias arising from the distribution of the ground truth (reference) partition against which candidate partitions are compared. We call this new type of bias ground truth (GT) bias. This type of bias occurs if a change in the reference partition causes a change in the bias status (e.g., NCinc, NCdec) of a CVI. For example, NCinc bias in the RI can be changed to NCdec bias by skewing the distribution of clusters in the ground truth partition. It is important for users to be aware of this new type of biased behaviour, since it may affect the interpretations of CVI results. The objective of this article is to study the empirical and theoretical implications of GT bias. To the best of our knowledge, this is the first extensive study of such a property for external cluster validity indices.

Researchers recently used an artificial intelligence to run a complex experiment, which it learnt to perform from scratch in under an hour. "A simple computer program would have taken longer than the age of the Universe to run through all the combinations and work this out," said co-lead researcher Paul Wigley from the Australian National University Research School of Physics and Engineering. This suggests that even physicists are on track to having their jobs augmented if not outright captured by artificial intelligence. The experiment involved the creation of a Bose-Einstein condensate, an extremely cold gas trapped in a laser beam. At a billionth of a degree Kelvin, it is even colder than outer space.

The increasing interest in complex networks research has been a consequence of several intrinsic features of this area, such as the generality of the approach to represent and model virtually any discrete system, and the incorporation of concepts and methods deriving from many areas, from statistical physics to sociology, which are often used in an independent way. Yet, for this same reason, it would be desirable to integrate these various aspects into a more coherent and organic framework, which would imply in several benefits normally allowed by the systematization in science, including the identification of new types of problems and the cross-fertilization between fields. More specifically, the identification of the main areas to which the concepts frequently used in complex networks can be applied paves the way to adopting and applying a larger set of concepts and methods deriving from those respective areas. Among the several areas that have been used in complex networks research, pattern recognition, optimization, linear algebra, and time series analysis seem to play a more basic and recurrent role. In the present manuscript, we propose a systematic way to integrate the concepts from these diverse areas regarding complex networks research. In order to do so, we start by grouping the multidisciplinary concepts into three main groups, namely features, similarity, and network connectivity. Then we show that several of the analysis and modeling approaches to complex networks can be thought as a composition of maps between these three groups, with emphasis on nine main types of mappings, which are presented and illustrated. Such a systematization of principles and approaches also provides an opportunity to review some of the most closely related works in the literature, which is also developed in this article.

Predicting ambulance demand accurately at a fine resolution in time and space (e.g., every hour and 1 km$^2$) is critical for staff / fleet management and dynamic deployment. There are several challenges: though the dataset is typically large-scale, demand per time period and locality is almost always zero. The demand arises from complex urban geography and exhibits complex spatio-temporal patterns, both of which need to captured and exploited. To address these challenges, we propose three methods based on Gaussian mixture models, kernel density estimation, and kernel warping. These methods provide spatio-temporal predictions for Toronto and Melbourne that are significantly more accurate than the current industry practice.

There is such a thing as the "IKEA effect," which, according to one description, suggests that "when individuals construct products themselves, they tend to overvalue their (often mediocre) creations." The "IKEA effect" highlights the importance of "self-agency": when you make something yourself, the work it takes to make that thing gives you a richer sense of initiative and ownership. The result is you get a more positive perception of your creation (even if it's made of particle board). Now two researchers from Pennsylvania State University's Media Effects Research Laboratory want to find out if the same thing applies to robots. The researchers, Yuan Sun and S. Shyam Sundar, say previous studies in human-computer interaction have demonstrated that the "self-agency" effect is present in things as basic as customizing the interface of a software application, resulting in "more positive attitudes toward the technology, a heightened sense of control and identity, greater user engagement, and product attachment."

Digital disruption has the potential to threaten 40 per cent of jobs over the next 10 to 15 years as automation and machine learning shake up the economy, according to a Productivity Commission report out today. In research entitled Digital Disruption: What do governments need to do?, the Commission warned that governments and regulators need to prepare for changing times as "disruption" moves beyond Uber and Air BnB. Productivity Commission chairman Peter Harris said developing disruptive technologies of machine intelligence and automation will gradually change economies. "There's little doubt that in some sectors there will be dislocation of labour and dislocation of capital. "It's not just a cost to employees, it will be a cost to certain businesses as well," Mr Harris told The World Today. "Things like 3D printing are going to have an impact.

Arria NLG PLC (LON:NLG), the language generation technology specialist, has confirmed it plans to raise further cash, probably via a listing on the New Zealand and Australian Stock Exchanges. In the half-yearly results statement it said it would also raise capital in the short-term "as needed". Last week it brought in 262,000 via the issue of loan notes and warrants. "The directors are confident of securing sufficient, additional funding within the next financial year, for its near term requirements," Arria said in the notes to its accounts. The results, meanwhile, showed the company had around 2.1mln in cash as at the end of March.

Ask five people who follow the video games industry what to expect from an E3 press conference and they'll all paint you a similar picture. Bright lights on a big stage, lengthy cinematic trailers for shooters starring gravelly-voiced stubble-faced white men, interspersed with awkward patter from white men in suits (or, depending on the publisher, suit jackets and T-shirts and trainers), cheered and whooped at by a largely white male audience. This industry is often unwelcoming to women and underrepresented minorities, and these widely watched events do little to counter that. Of course, some conferences do better than others. This year, we've judged EA, Bethesda, Microsoft, Ubisoft, and Sony for the diversity of their speakers and of the games and characters on show.