If you're still emotionally wiped out by Avengers Endgame, The Void and ILMxLAB's latest VR entry might soothe your geeky soul. Avengers Damage Control is more than just a mere virtual reality game, like the upcoming Iron Man title for the PlayStation VR. Instead, it's a prime example of what The Void does best: Building large-scale multi-player VR experiences mapped to physical sets. It's a dream come true for anyone who's ever wanted to fight alongside their favorite Marvel superheroes -- just be prepared to shell out $40 to experience it. Suiting up for Damage Control involves strapping on one of The Void's backpack computers, as well as a huge VR headset.

Newswire) GBT Technologies Inc. (OTCPINK: GTCH) ("GBT", or the "Company"), a company specializing in the development of Internet of Things (IoT) and Artificial Intelligence (AI) enabled networking and tracking technologies, including its GopherInsight wireless mesh network technology platform and its Avant! AI, for both mobile and fixed solutions, announced that it is now adding the first elements of cognitive features within its AI expert agent. The agent now includes feedback features, i.e. "thumbs up" and "thumbs down", that work with the artificial neural network mechanism to learn and improve answers' accuracy and their relationship to the topic. The user feedback is fed into the Avant! RNN (Recurrent Neural Network), which synthesizes data from various information sources, weighing and comparing the feedback to the answer context to provide the best, most accurate answers.

Knowledge Graphs (KGs) are composed of structured information about a particular domain in the form of entities and relations. In addition to the structured information KGs help in facilitating interconnectivity and interoperability between different resources represented in the Linked Data Cloud. KGs have been used in a variety of applications such as entity linking, question answering, recommender systems, etc. However, KG applications suffer from high computational and storage costs. Hence, there arises the necessity for a representation able to map the high dimensional KGs into low dimensional spaces, i.e., embedding space, preserving structural as well as relational information. This paper conducts a survey of KG embedding models which not only consider the structured information contained in the form of entities and relations in a KG but also the unstructured information represented as literals such as text, numerical values, images, etc. Along with a theoretical analysis and comparison of the methods proposed so far for generating KG embeddings with literals, an empirical evaluation of the different methods under identical settings has been performed for the general task of link prediction.

The traditional offline approaches are no longer sufficient for building modern recommender systems in domains such as online news services, mainly due to the high dynamics of environment changes and necessity to operate on a large scale with high data sparsity. The ability to balance exploration with exploitation makes the multi-armed bandits an efficient alternative to the conventional methods, and a robust user segmentation plays a crucial role in providing the context for such online recommendation algorithms. In this work, we present an unsupervised and trend-responsive method for segmenting users according to their semantic interests, which has been integrated with a real-world system for large-scale news recommendations. The results of an online A/B test show significant improvements compared to a global-optimization algorithm on several services with different characteristics. Based on the experimental results as well as the exploration of segments descriptions and trend dynamics, we propose extensions to this approach that address particular real-world challenges for different use-cases. Moreover, we describe a method of generating traceable publishing insights facilitating the creation of content that serves the diversity of all users needs.

Microsoft technology brings Ben-Gurion's writings alive.

Until a few years ago, people queued at the bank, booked their holidays off brochures, paid their bills in cash, bought their music on CDs and waited in line at outpatient departments to see a doctor. People bank and book holidays online, use Revolut and PayPal to settle bills, and Spotify their music. Yet, they still wait in line at outpatient departments to see a doctor. The question practically asks itself. Why hasn't the'consumer revolution' reached the healthcare doorstep?

Will androids write novels about electric sheep? The dream, or nightmare, of totally machine-generated prose seemed to have come one step closer with the recent announcement of an artificial intelligence that could produce, all by itself, plausible news stories or fiction. It was the brainchild of OpenAI – a nonprofit lab backed by Elon Musk and other tech entrepreneurs – which slyly alarmed the literati by announcing that the AI (called GPT2) was too dangerous for them to release into the wild, because it could be employed to create "deepfakes for text". "Due to our concerns about malicious applications of the technology," they said, "we are not releasing the trained model." Are machine-learning entities going to be the new weapons of information terrorism, or will they just put humble midlist novelists out of business?

Stuart Russell has a rule. "I won't do an interview until you agree not to put a Terminator on it," says the renowned British computer scientist, sitting in a spare room at his home in Berkeley, California. "The media is very fond of putting a Terminator on anything to do with artificial intelligence." The request is a tad ironic. Russell, after all, was the man behind Slaughterbots, a dystopian short film he released in 2017 with the Future of Life Institute.