On 25 April, Zooniverse launched a website that asks volunteers to analyse rapidly-snapped satellite imagery of the disaster, which led to more than 650 reported deaths and 16,000 injuries. The aim is to help relief workers on the ground to find the most heavily damaged regions and identify which roads are passable. Several crisis-mapping programmes with thousands of volunteers already exist -- but it can take days to train satellites on the damaged region and to transmit data to humanitarian organizations, and results have not always proven useful. The Ecuador quake marked the first live public test for an effort dubbed the Planetary Response Network (PRN), which promises to be both more nimble than previous efforts, and to use more rigorous machine-learning algorithms to evaluate the quality of crowd-sourced analyses. The network relies on imagery from the satellite company Planet Labs in San Francisco, California, which uses an array of shoebox-sized satellites to map the planet.

This is the leading international symposium where the Ibero-American AI community comes together to share research results and experiences with researchers in Artificial Intelligence from all over the world. The conference will feature a pre-conference program of workshops. The main technical program will consist of invited talks by leading scientists working in the area, presentations of technical papers, as well as system demonstrations. The Proceedings of IBERAMIA 2016 will be published, as in past editions, by Springer in its Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence LNCS/LNAI series. IBERAMIA 2016, the XV edition of IBERAMIA, welcomes submissions on mainstream AI topics, as well as novel cross cutting work in related areas.

After being stranded in the Mediterranean for three days, fear had overcome Alou Sango. "I thought that we would all die, because there was nothing left, the petrol had finished," he says of his journey from Libya. Like thousands before him, Sango boarded an overcrowded boat to escape the country's turmoil after being unable to return to his native Mali. But after days at sea the captain lost his way and, without a GPS position to give to the Italian authorities, the 100 or so passengers were losing hope. Their rubber dinghy was finally spotted by a Chinese vessel, which picked up the migrants and took them to Italy, where Sango, now 24, is studying through a Rome-based charity, Sant'Egidio Community.

Did you know there is a 25% chance your cause of death will be due to environmental pollution? According the World Health Organization, some 12.6 million people--or nearly 1 in 4 worldwide--died in 2012 due to living or working in unhealthy conditions. In addition, environmental degradation seriously affects overall quality of life and the balance of Earth's ecosystems through loss of forests, open spaces, marine environments and biodiversity. While technological growth and industrialization historically contributed to such problems, the latest technologies--from robotics to artificial intelligence to biotechnology--will also help create healthier and greener industries benefiting both people and planet. While affordable electric and hybrid cars will help reduce pollution and use of fossil fuels, self-driving cars will make our whole transportation and logistics systems more efficient. Cars, trucks, ships, drones and jets that drive or pilot themselves and wirelessly communicate with each other can coordinate and optimize delivery of people and goods in ways requiring less energy.

Autonomous cars are a chance to reinvent the steering wheel. Because the vehicles themselves do all the driving, cars are no longer bound by such basic conventions as "keep a human facing forward at all times" and "don't try to climb over boulders like a spider." As a grand showcase for the new possibilities of autonomous cars, Honda plotted a seven-stage road trip roughly following that path of humanity's great migration from a species to the edge of the world. The auto company used miniature models for this conceptual video, but the hope is the same principles could be applied to human-sized autonomous vehicles of the future. Honda's route goes from Nairobi, Kenya to Manaus, Brazil, and new vehicles trace individual legs of that journey.

We present a theoretical analysis and empirical evaluations of a novel set of techniques for computational cost reduction of classifiers that are based on learned transform and soft-threshold. By modifying optimization procedures for dictionary and classifier training, as well as the resulting dictionary entries, our techniques allow to reduce the bit precision and to replace each floating-point multiplication by a single integer bit shift. We also show how the optimization algorithms in some dictionary training methods can be modified to penalize higher-energy dictionaries. We applied our techniques with the classifier Learning Algorithm for Soft-Thresholding, testing on the datasets used in its original paper. Our results indicate it is feasible to use solely sums and bit shifts of integers to classify at test time with a limited reduction of the classification accuracy. These low power operations are a valuable trade off in FPGA implementations as they increase the classification throughput while decrease both energy consumption and manufacturing cost.

The summer school occurs at the first two weeks of the Third Frederick Jelinek Memorial Summer Workshop. The North American Chapter of the Association for Computational Linguistics (NAACL) is again offering an exciting summer school opportunity for a limited number of undergraduate students interested in the field of Human Language Technology. The 2016 Jelinek Summer Workshop will be held from Monday, June 13 to Friday, August 5, 2016 at the Johns Hopkins University in Baltimore, Maryland. The first two weeks of the workshop (from June 13 to 24) is a summer school that provides general introductions to the major areas of study within the field of Human Language Technology (e.g., Natural Language Processing, Automatic Speech Recognition, Machine Translation, Information Retrieval) as well as sessions on specialized research topics of current interest in the field. The NAACL scholarship is used to support undergraduate students to participate in the two-week summer school.

Visualization of high-dimensional data, such as text documents, is useful to map out the similarities among various data points. In the high-dimensional space, documents are commonly represented as bags of words, with dimensionality equal to the vocabulary size. Classical approaches to document visualization directly reduce this into visualizable two or three dimensions. Recent approaches consider an intermediate representation in topic space, between word space and visualization space, which preserves the semantics by topic modeling. While aiming for a good fit between the model parameters and the observed data, previous approaches have not considered the local consistency among data instances. We consider the problem of semantic visualization by jointly modeling topics and visualization on the intrinsic document manifold, modeled using a neighborhood graph. Each document has both a topic distribution and visualization coordinate. Specifically, we propose an unsupervised probabilistic model, called Semafore, which aims to preserve the manifold in the lower-dimensional spaces through a neighborhood regularization framework designed for the semantic visualization task. To validate the efficacy of Semafore, our comprehensive experiments on a number of real-life text datasets of news articles and Web pages show that the proposed methods outperform the state-of-the-art baselines on objective evaluation metrics.

It's that time of year: The most prepared of you are carboloading after weeks of training for Marathon Monday, while the least prepared are scrambling to finish your taxes. Either way, surely you'll need some breaks in the pasta and accounting. Should you take your kids to Disney's live-action/CGI remake of its beloved 1967 film "The Jungle Book"? Absolutely, says Ty Burr, who gives three stars to this movie placing "talking animals of almost tactile musculature and movement" in a lush jungle landscape; it holds up right until its overly frenetic final scenes. The jungle beasts are voiced by the likes of Ben Kingsley, Lupita Nyong'o, Bill Murray, Idris Elba, and Scarlett Johanssen, and newcomer Neel Sethi is charming as Mowgli.

The future of food looks a lot like advanced animal product substitutes; we've already gone beyond tofurkey to plant-based burgers that "bleed." Down in Santiago, Chile, a five-person startup is using machine learning to figure out how to create its own versions of vegetarian substitutes for animal products. Called the Not Company (or NotCo), the one-year-old company is rolling out its first products -- NotMilk, NotMayo. "All I can tell you is that there are some star ingredients ranging from legumes to flowers," NotCo cofounder Matias Muchnick tells Tech Insider. Machine learning, the programming technique where algorithms learn from data sets, has become the hot new thing in Silicon Valley.