The fragile apparition endured only long enough to say: "Help me Obi Wan Kenobi, you're my only hope" before flickering out. But R2D2's 3D projection gave millions of young eyes, including mine, their first taste of holograms, and planted unrealistic expectations of a future playing dejarik, the gruesome game of holographic chess played on board the Millennium Falcon. The concept of the hologram was already familiar, invented in the 1940s by physicist Dennis Gabor, but since the force reawakened the idea almost 40 years later, things haven't really moved on. That depends on your definition of a hologram. We have made astounding strides in 3D TV and virtual reality, and in the eye-twistingly complex world of computer-generated holography (CGH) – simply put, a way of recording and reproducing 3D images on a medium like standard images on film.

WASHINGTON: For its updated news application, Google is doubling down on the use of artificial intelligence as part of an effort to weed our disinformation and help users get viewpoints beyond their own "filter bubble." Google chief Sundar Pichai, who unveiled the updated Google News earlier this month, said the app now "surfaces the news you care about from trusted sources while still giving you a full range of perspectives on events." It marks Google's latest effort to be at the center of online news and includes a new push to help publishers get paid subscribers through the tech giant's platform. According to product chief Trystan Upstill, the news app "uses the best of artificial intelligence to find the best of human intelligence -- the great reporting done by journalists around the globe." While the app will enable users to get "personalized" news, it will also include top stories for all readers, aiming to break the so-called filter bubble of information designed to reinforce people's biases.

The Tokyo-based maker of the Walkman portable player, Aibo entertainment robot and Bravia TVs has amassed know-how over the decades when it was leading in "analog technology," said Yoshida, who was named president and chief executive in February. He said Sony's CMOS image sensor excels in its speed, lighting range and absence of noise.

In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects on the offline society already. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance. This paper addresses the challenges introduced by the unknown characteristics of fake news and diverse connections among news articles, creators and subjects. Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector. Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously. Extensive experiments have been done on a real-world fake news dataset to compare FakeDetector with several state-of-the-art models, and the experimental results have demonstrated the effectiveness of the proposed model.

Long-Short-Term-Memory Recurrent Neural Network (LSTM RNN) is a state-of-the-art (SOTA) model for analyzing sequential data. Current implementations of LSTM RNN in machine learning frameworks usually either lack performance or flexibility. For example, default implementations in Tensorflow and MXNet invoke many tiny GPU kernels, leading to excessive overhead in launching GPU threads. Although cuDNN, NVIDIA's deep learning library, can accelerate performance by around 2x, it is closed-source and inflexible, hampering further research and performance improvements in frameworks, such as PyTorch, that use cuDNN as their backend. In this paper, we introduce a new RNN implementation called EcoRNN that is significantly faster than the SOTA open-source implementation in MXNet and is competitive with the closed-source cuDNN. We show that (1) fusing tiny GPU kernels and (2) applying data layout optimization can give us a maximum performance boost of 3x over MXNet default and 1.5x over cuDNN implementations. Our optimizations also apply to other RNN cell types such as LSTM variants and Gated Recurrent Units (GRUs). We integrate EcoRNN into MXNet Python library and open-source it to benefit machine learning practitioners.

This paper reconstructs the Freebase data dumps to understand the underlying ontology behind Google's semantic search feature. The Freebase knowledge base was a major Semantic Web and linked data technology that was acquired by Google in 2010 to support the Google Knowledge Graph, the backend for Google search results that include structured answers to queries instead of a series of links to external resources. After its shutdown in 2016, Freebase is contained in a data dump of 1.9 billion Resource Description Format (RDF) triples. A recomposition of the Freebase ontology will be analyzed in relation to concepts and insights from the literature on classification by Bowker and Star. This paper will explore how the Freebase ontology is shaped by many of the forces that also shape classification systems through a deep dive into the ontology and a small correlational study. These findings will provide a glimpse into the proprietary blackbox Knowledge Graph and what is meant by Google's mission to "organize the world's information and make it universally accessible and useful".

Speaking in Macclesfield, the Prime Minister will use a speech to challenge the NHS, Artificial Intelligence (AI) sector and health charities to use data and AI to transform the diagnosis of chronic diseases.

With both ARKit and ARCore available to the public, augmented reality is now enabled on over 500 million devices. There are over 2,000 AR apps available in iOS App Store and another 200-plus on Google Play. With few breakout hits, many are wondering what the killer use cases for AR will be. We can examine the growth of the mobile app ecosystem to better understand how mobile AR will evolve. The growth of the mobile ecosystem was driven, in part, by three use cases: Creative, Contextual and Connected apps.

Earlier this month, Google's Chief Executive Officer Sundar Pichai unveiled the new and improved Google News. According to Pichai, the app could now show "the news you care about from trusted sources while still giving you a full range of perspectives on events." The company is reportedly working on integrating artificial intelligence in its news app in an effort to eliminate disinformation and help people get more viewpoints that are beyond their so-called "filter bubble." The new initiative was said to be part of Google's goal to be at the center of online news. This also includes new efforts to help advertisers and publishers gain paid subscribers using the tech company's platform. Google's product chief Trystan Upstill also added that the Google News would make use of the "best artificial intelligence to find the best of human intelligence," which, according to Google, is the reporting done by local and international journalists.

The Basware Assistant uses natural language processing and artificial intelligence to create a new and simplified way for people to interact with Basware's e-procurement solution. They can communicate with the Basware Assistant like they would with a person, to search for orders and purchase requests using vendor and item names, as well as ID and document numbers. By giving people the ability to specify what they are looking, it eliminates the need for having to navigate a series of screens to reach their intended purchase. Through its natural language processing and AI capabilities, the virtual assistant improves system usability, taking another step in streamlining the overall procurement experience. Not only does it help people find purchase orders and order requests more quickly and save them time, it also reduces the training required for new people to buy with Basware.