Donald Trump has accused Google of rigging its search results to make him look bad. People who search for the latest news about the president are in fact being shown intentionally damaging stories, he claimed. Mr Trump even suggested that the results could be getting illegally manipulated from inside the search giant. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Shot-for-shot remakes are a dangerous proposition for any filmmaker. The potential downsides are huge--see, e.g., Gus Van Sant's Psycho or John Legend and Stevie Wonder's "Hey Ya!"--and the upside is tiny. Even excellent remakes, like Jimmy Fallon's meticulous recreation of the music video for Styx's "Too Much Time on My Hands," can only hope to be praised for their attention to detail, not their artistic vision. There is one exception, however: remakes that replace the film's original humans with live-action house pets behaving like humans. These are uniformly masterpieces, each and every time, and it is incumbent upon critics to bring them to the attention of as large an audience as possible as quickly as possible.

One of the complaints I recently had with Bing's ability to search news involved its seeming inability to generate search results with sufficient information density. On Monday, Bing coincidentally released a new "spotlight" feature that promises to help. The Bing spotlight feature consists of three different areas: a timeline that tracks major evolutions in the story or topic, and various news perspectives, as well as the large "hero" image that features breaking news. Both perspectives and stories are compiled using a combination of both AI and experienced human editors, according to Bing. According to Bing, the site tracks "queries and browser logs, and document signals from publishers such as how many publishers cover a story, their angles, and how prominently they feature the story on their site."

Cross-domain collaborative filtering (CF) aims to alleviate data sparsity in single-domain CF by leveraging knowledge transferred from related domains. Many traditional methods focus on enriching compared neighborhood relations in CF directly to address the sparsity problem. In this paper, we propose superhighway construction, an alternative explicit relation-enrichment procedure, to improve recommendations by enhancing cross-domain connectivity. Specifically, assuming partially overlapped items (users), superhighway bypasses multi-hop inter-domain paths between cross-domain users (items, respectively) with direct paths to enrich the cross-domain connectivity. The experiments conducted on a real-world cross-region music dataset and a cross-platform movie dataset show that the proposed superhighway construction significantly improves recommendation performance in both target and source domains.

Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios. Current approaches either only handle off-line trajectory generation, or offer strategies that reason over short time horizons and simplistic representations for obstacles, which result in jerky movement and low real-life applicability. In this work we develop a method for aerial filming that is able to trade off shot smoothness, occlusion, and cinematography guidelines in a principled manner, even under noisy actor predictions. We present a novel algorithm for real-time covariant gradient descent that we use to efficiently find the desired trajectories by optimizing a set of cost functions. Experimental results show that our approach creates attractive shots, avoiding obstacles and occlusion 65 times over 1.25 hours of flight time, re-planning at 5 Hz with a 10 s time horizon. We robustly film human actors, cars and bicycles performing different motion among obstacles, using various shot types.

A new AI can make anybody look like a dance superstar by giving them the moves of a professional dancer. The creepy robot uses the movements of top dancers captured from a video to animate your body in a creepy'DeepFake'-style video. Experts behind the technology said it allows amateurs to'twirl like ballerinas', or perfectly imitate their favourite pop stars. A new AI can make anybody look like a dance superstar by giving them the moves of a professional dancer. The creepy robot uses the movements of top dancers (left) captured from a video to animate your body (right images) in a creepy'DeepFake'-style video The AI, developed by researchers at the University of California at Berkeley, first copies the moves of a professional dancer from a source video.

Experts from scores of countries are meeting to discuss ways to define and deal with "killer robots" _ futuristic weapons systems that could conduct war without human intervention.

The gadgets we think of as home essentials have changed beyond recognition in the past few decades. In 1970, just 35 per cent of homes had a landline telephone and there were no mobiles. Now, technologies that were once the stuff of science fiction are part of our daily lives: take Amazon's Alexa – inspired by the talking computer on the Starship Enterprise in Star Trek. Today, millions of British households own these'smart speakers' that allow voice commands to control everything from TVs to lighting systems. Indeed, as of this year, one in five households will be'smart', with devices that are wirelessly connected to the internet, and controlled via smartphone or a hub.

AI and robotics are going to shape our future. Next there are 10 issues that professionals and researchers need to address in order to desing intelligent systems that help humanity. The flow of misinformation together with our natural inability of perceiving reality based on evidence (a phenomenon called confirmation bias) is a threat to having an informed democracy. Russian hackers influencing the US elections, Brexit campaign and Catalonia crisis are examples of how social media can massively spread misinformation and fake news. It is an open question how institutions are going to address this threat. The scientific revolution in the 18th century and the industrial revolution in the 19th marked a complete change in society.

In this work, we ask two questions: 1. Can we predict the type of community interested in a news article using only features from the article content? and 2. How well do these models generalize over time? To answer these questions, we compute well-studied content-based features on over 60K news articles from 4 communities on reddit.com. We train and test models over three different time periods between 2015 and 2017 to demonstrate which features degrade in performance the most due to concept drift. Our models can classify news articles into communities with high accuracy, ranging from 0.81 ROC AUC to 1.0 ROC AUC. However, while we can predict the community-specific popularity of news articles with high accuracy, practitioners should approach these models carefully. Predictions are both community-pair dependent and feature group dependent. Moreover, these feature groups generalize over time differently, with some only degrading slightly over time, but others degrading greatly. Therefore, we recommend that community-interest predictions are done in a hierarchical structure, where multiple binary classifiers can be used to separate community pairs, rather than a traditional multi-class model. Second, these models should be retrained over time based on accuracy goals and the availability of training data.