Snapchat Inc. is in the process of acquiring personalized search app Vurb, according to people familiar with matter. The Venice entertainment app maker would spend more than 100 million in cash and stock to purchase the San Francisco start-up, said a source unauthorized to speak publicly about the deal. The transaction hasn't been finalized, multiple sources said. Vurb co-founder and Chief Executive Bobby Lo would receive 75 million over several years -- separate from the initial purchase price -- if he stays at Snapchat. The tech news website the Information first reported details of the deal Monday.

SpaceX launched JCSAT-16 from Cape Canaveral Air Force Station and landed the first stage on a drone ship in the Atlantic Ocean. A United Launch Alliance Atlas V rocket blasted off from Cape Canaveral Air Force Station on Thursday, July 28, 2016 with a secret payload for the National Reconnaissance Office. SpaceX successfully launched its Falcon 9 rocket from Cape Canaveral and landed it about eight minutes later. United Launch Alliance launched an Atlas V rocket at 10:30 a.m. SpaceX launched a pair of communications satellites from Cape Canaveral on Wednesday, but it was unknown if the first stage landed successfully.

Do machine-learning algorithms processing search engine queries bring on prejudice, discrimination and stereotyping in query results? Search results have been known to highlight these negative attributes in the past. Now researchers at Brazil's Universidade Federal de Minas Gerais suggest it could be true when it comes to female physical attractiveness in images available across the Web. The paper submitted to the International Conference on Social Informatics scheduled for publication analyzes how Google and Bing represent female beauty in their image search results, particularly when it comes to different age and racial groups. They then passed the more than 2,000 images through a program, which estimates subject age, race and gender with an estimated 90% accuracy.

This guest article was written by Dr. Cleber Gomes who is an Electronic Engineer with a Ph.D. from Tokyo University of Technology and Agriculture. As we approach the date of the Impeachment vote in Brazil, it might be interesting to take a look at how the Brazilian stock market behaves. In this article, I propose to do that from the point of view of Trend Following Algorithms. To exemplify, I will present the results acquired from my own Trend Following System, which is based on Machine Learning technologies, specifically Neural Networks. Take the lead from today's leaders.

The following is a condensed and edited interview with Ginni Rometty, CEO, IBM. You joined IBM 35 years ago. What was the company like back then? What struck me was the seriousness of the kind of things we did. We were building complex back-office banking systems.

Scientists with the international scientific collaboration known as the "Walk Again Project" use noninvasive brain-machine interfaces in their efforts to reawaken damaged fibers in the spinal cord. Scientists with the international scientific collaboration known as the "Walk Again Project" use noninvasive brain-machine interfaces in their efforts to reawaken damaged fibers in the spinal cord. Researchers in Brazil who are trying to help people with spine injuries gain mobility have made a surprising discovery: Injured people doing brain training while interacting with robot-like machines were able to regain some sensation and movement. The findings, published in Scientific Reports (one of the Nature journals), suggest that damaged spinal tissue in some people with paraplegia can be retrained to a certain extent -- somewhat the way certain people can regain some brain function following stroke though repetition and practice. Even people with severe injuries can regain some sensation and function through physical therapy if some nerve fibers remain.

The invention of religion is a big bang in human history. Gods and spirits helped explain the unexplainable, and religious belief gave meaning and purpose to people struggling to survive. But what if everything we thought we knew about religion was wrong? What if belief in the supernatural is window dressing on what really matters--elaborate rituals that foster group cohesion, creating personal bonds that people are willing to die for. Anthropologist Harvey Whitehouse thinks too much talk about religion is based on loose conjecture and simplistic explanations. Whitehouse directs the Institute of Cognitive and Evolutionary Anthropology at Oxford University. For years he's been collaborating with scholars around the world to build a massive body of data that grounds the study of religion in science. Whitehouse draws on an array of disciplines--archeology, ethnography, history, evolutionary psychology, cognitive science--to construct a profile of religious practices. Whitehouse's fascination with religion goes back to his own groundbreaking field study of traditional beliefs in Papua New Guinea in the 1980s.

Techniques such as clusterization, neural networks and decision making usually rely on algorithms that are not well suited to deal with missing values. However, real world data frequently contains such cases. The simplest solution is to either substitute them by a best guess value or completely disregard the missing values. Unfortunately, both approaches can lead to biased results. In this paper, we propose a technique for dealing with missing values in heterogeneous data using imputation based on the k-nearest neighbors algorithm. It can handle real (which we refer to as crisp henceforward), interval and fuzzy data. The effectiveness of the algorithm is tested on several datasets and the numerical results are promising.

Time-Bounded A* is a real-time, single-agent, deterministic search algorithm that expands states of a graph in the same order as A* does, but that unlike A* interleaves search and action execution. Known to outperform state-of-the-art real-time search algorithms based on Korf's Learning Real-Time A* (LRTA*) in some benchmarks, it has not been studied in detail and is sometimes not considered as a ``true'' real-time search algorithm since it fails in non-reversible problems even it the goal is still reachable from the current state. In this paper we propose and study Time-Bounded Best-First Search (TB(BFS)) a straightforward generalization of the time-bounded approach to any best-first search algorithm. Furthermore, we propose Restarting Time-Bounded Weighted A* (TB_R(WA*)), an algorithm that deals more adequately with non-reversible search graphs, eliminating ``backtracking moves'' and incorporating search restarts and heuristic learning. In non-reversible problems we prove that TB(BFS) terminates and we deduce cost bounds for the solutions returned by Time-Bounded Weighted A* (TB(WA*)), an instance of TB(BFS). Furthermore, we prove TB_R(WA*), under reasonable conditions, terminates. We evaluate TB(WA) in both grid pathfinding and the 15-puzzle. In addition, we evaluate TB_R(WA*) on the racetrack problem. We compare our algorithms to LSS-LRTWA*, a variant of LRTA* that can exploit lookahead search and a weighted heuristic. A general observation is that the performance of both TB(WA*) and TB_R(WA*) improves as the weight parameter is increased. In addition, our time-bounded algorithms almost always outperform LSS-LRTWA* by a significant margin.

Since the dawn of manufacturing, designers and engineers have repeatedly run up against limitations to making things. Their ability to execute and capacity to afford bringing their ideas to market were once constrained by the manufacturing facility they had to find--either local or offshore--to build the things they wanted to build. But in a new world of enhanced robotics, factory automation, 3D printing, generative design, and design-make-use convergence, engineers' project limitations will fade away. And it's all because machine learning, computing power, and robots in the workforce are increasingly capable and intelligent. Soon, engineers will be able to design the best thing possible and then hand it to robots to dissect and turn into a series of assembled 3D-printed components.