Stunning drone footage has revealed the incredible progress on the Large Synoptic Survey Telescope – a massive instrument that will one day produce the'deepest, widest image of the universe' ever captured. Construction on the telescope in Chile began in 2015, with plans for it to begin operations around 2022. Now, nearly three years later, the new video shows how the enormous mountaintop facility has begun to take shape. Stunning drone footage has revealed the incredible progress on the Large Synoptic Survey Telescope – a massive instrument that will one day produce the'deepest, widest image of the universe' ever captured The video, published this week by the LSST team, was submitted by Assembly Integration Verification Manager Jacques Sebag, who captured the amazing view using a drone. At the time, the team was working with subcontractor Besalco to move the facility's mobile roof to a flatter area on the north side of the building.

The world's top 32 drone pilots will compete Saturday in Las Vegas for the world champion title in the International Drone Racing Assn.'s top challenge. Semi-professionals wearing virtual reality headgear compete for a $50,000 cash prize in the Challengers Cup Final on Friday and Saturday at the South Point hotel-casino at 9777 S. Las Vegas Blvd. Competitors qualified during 2017 races that began in Buenos Aires, Argentina, and concluded in Manila, the Philippines. Visitors can buy tickets to watch for $20. You'll be admitted to Friday's practice runs and the competition on Saturday afternoon. The elimination round will get underway at 12:30 p.m. with the finals set for 3:20 p.m. Saturday.

Australian-based TrademarkVision developed a deep learning-based reverse visual search platform that protects your brand by identifying similar trademarks from around the world. Simply upload your image to the platform, and their image recognition technology will compare it against other trademarked logos – making it much easier to identify IP infringements than the previous time-consuming and costly text-based search process. "Our technology not only makes it easy for an entrepreneur with a new design to ensure it is unique, but also enables the largest of companies to monitor for infringement," explains Cameron Mitchell, the Chief Operations Officer of TrademarkVision. The young startup has already integrated their technology with the intellectual property departments in the EU, Australia, Chile and more. Most recently, they launched a visual search for industrial designs.

We consider the task of weakly supervised one-shot detection. In this task, we attempt to perform a detection task over a set of unseen classes, when training only using weak binary labels that indicate the existence of a class instance in a given example. The model is conditioned on a single exemplar of an unseen class and a target example that may or may not contain an instance of the same class as the exemplar. A similarity map is computed by using a Siamese neural network to map the exemplar and regions of the target example to a latent representation space and then computing cosine similarity scores between representations. An attention mechanism weights different regions in the target example, and enables learning of the one-shot detection task using the weaker labels alone. The model can be applied to detection tasks from different domains, including computer vision object detection. We evaluate our attention Siamese networks on a one-shot detection task from the audio domain, where it detects audio keywords in spoken utterances. Our model considerably outperforms a baseline approach and yields a 42.6% average precision for detection across 10 unseen classes. Moreover, architectural developments from computer vision object detection models such as a region proposal network can be incorporated into the model architecture, and results show that performance is expected to improve by doing so.

The field of Multi-Agent System (MAS) is an active area of research within Artificial Intelligence, with an increasingly important impact in industrial and other real-world applications. Within a MAS, autonomous agents interact to pursue personal interests and/or to achieve common objectives. Distributed Constraint Optimization Problems (DCOPs) have emerged as one of the prominent agent architectures to govern the agents' autonomous behavior, where both algorithms and communication models are driven by the structure of the specific problem. During the last decade, several extensions to the DCOP model have enabled them to support MAS in complex, real-time, and uncertain environments. This survey aims at providing an overview of the DCOP model, giving a classification of its multiple extensions and addressing both resolution methods and applications that find a natural mapping within each class of DCOPs. The proposed classification suggests several future perspectives for DCOP extensions, and identifies challenges in the design of efficient resolution algorithms, possibly through the adaptation of strategies from different areas.

The present paper aims to demonstrate the usage of Convolutional Neural Networks as a generative model for stochastic processes, enabling researchers from a wide range of fields - such as quantitative finance and physics - to develop a general tool for forecasts and simulations without the need to identify/assume a specific system structure or estimate its parameters.

Chile's Atacama Desert makes for great stargazing. The dry air and sparse settlement are a major draw for astronomical observatories--the European Southern Observatory, the Carnegie Institution for Science, and the Llano de Chajnantor Observatory all operate multiple telescope sites on the region's mountaintops. The desert wind, however, is a problem. The air rushes around and through the enclosures that hold these massive but sensitive, precise instruments. Typically, observatories have responded with heavy mounts and robust structures that keep the mirrors steady amid the turbulence.

Didi Chuxing, the ride-sharing giant of China and likely the most valuable startup in the world, just bought a controlling stake in 99, a leading ride-sharing app in Brazil. Didi already had a minority stake in the startup, having invested $100 million over a year ago. "Globalization is a top strategic priority for Didi," Cheng Wei, founder and CEO of Didi, said in a statement. "With enhanced investments in AI capabilities and smart transportation solutions, we will continue to advance the transformation of global transportation and automotive industries through diversified international operations and partnerships." The news follows the announcement that Didi plans to expand into Mexico in 2018, intensifying its global rivalry with Uber.

Recently, linear formulations and convex optimization methods have been proposed to predict diffusion-weighted Magnetic Resonance Imaging (dMRI) data given estimates of brain connections generated using tractography algorithms. The size of the linear models comprising such methods grows with both dMRI data and connectome resolution, and can become very large when applied to modern data. In this paper, we introduce a method to encode dMRI signals and large connectomes, i.e., those that range from hundreds of thousands to millions of fascicles (bundles of neuronal axons), by using a sparse tensor decomposition. We show that this tensor decomposition accurately approximates the Linear Fascicle Evaluation (LiFE) model, one of the recently developed linear models. We provide a theoretical analysis of the accuracy of the sparse decomposed model, LiFESD, and demonstrate that it can reduce the size of the model significantly. Also, we develop algorithms to implement the optimisation solver using the tensor representation in an efficient way.

LUIS is now generally available in the Australia East, Brazil South, West US 2, South Central US, East US, East Asia, and North Europe regions, in addition to the current availability in the East US 2, West Central US, West US, West Europe, and Southeast Asia regions. General availability (GA) pricing will begin on February 1, 2018. Usage prior to February 1, 2018, will be billed at preview rates.