Video analytics powered by artificial intelligence (AI) simplifies and accelerates that process.

He said that the programme also provides the feedback with the help of artificial intelligence.

Just down the block, inside a stone building of its own, Microsoft is designing some sort of computer chip for artificial intelligence.

When a man in the Middle East appears to be performing miracles, a rift breaks out over whether he's the Messiah or a fraud in this suspenseful drama.

His groundbreaking application of advanced artificial intelligence algorithms for the analysis, transformation and creation of music forms the basis of DigiTrax's disruptive approach to music composition, and has generated seven granted patents. As the software architect of The Music Builder platform, his pioneering vision is grounded in both theoretical and practical knowledge of music theory. Mr. Matusiak has garnered multiple awards in the field, while completing his studies at Leeds College of Music in the U.K.

Abstract: We demonstrate the first application of deep reinforcement learning to autonomous driving. From randomly initialised parameters, our model is able to learn a policy for lane following in a handful of training episodes using a single monocular image as input. We provide a general and easy to obtain reward: the distance travelled by the vehicle without the safety driver taking control. We use a continuous, model-free deep reinforcement learning algorithm, with all exploration and optimisation performed on-vehicle. This demonstrates a new framework for autonomous driving which moves away from reliance on defined logical rules, mapping, and direct supervision.

Knowledge graphs encode uniquely identifiable entities to other entities or literal values by means of relationships, thus enabling semantically rich querying over the stored data. Typically, the semantics of such queries are often crisp thereby resulting in crisp answers. Query log statistics show that a majority of the queries issued to knowledge graphs are often entity centric queries. When a user needs additional answers the state-of-the-art in assisting users is to rewrite the original query resulting in a set of approximations. Several strategies have been proposed in past to address this. They typically move up the taxonomy to relax a specific element to a more generic element. Entities don't have a taxonomy and they end up being generalized. To address this issue, in this paper, we propose an entity centric reformulation strategy that utilizes schema information and entity features present in the graph to suggest rewrites. Once the features are identified, the entity in concern is reformulated as a set of features. Since entities can have a large number of features, we introduce strategies that select the top-k most relevant and {informative ranked features and augment them to the original query to create a valid reformulation. We then evaluate our approach by showing that our reformulation strategy produces results that are more informative when compared with state-of-the-art

Katherine Nails is a former eZanga Content Marketing Intern. She is a student at the University of Delaware, where she is pursuing a Bachelor of Arts in Media Communication, and minors in Journalism and Integrated Design. When she's not tracking down a source for her school's student newspaper, you can find her relaxing with a good book or movie.