Artificial intelligence (AI) has become a key area of research and development, and while AI and machine learning algorithms begin to influence everything from our cars to our social media news feeds, the technology will soon be available to everyone. That is if Gartner's predictions on emerging technology trends prove to be true. On Monday, the research agency said that democratized AI will be one of the major trends which will shape our future technologies. The research is based on the so-called "Hype Cycle," which comprises of insights from over 2,000 technologies into 35 main areas of interest and trends, with a particular focus on innovations which could give businesses a future competitive advantage. Gartner says that AI technologies will be "virtually everywhere" over the next 10 years, but it will be open to the masses rather than being purely commercial.

The chief economist of the Bank of England has warned that the UK will need a skills revolution to avoid "large swathes" of people becoming "technologically unemployed" as artificial intelligence makes many jobs obsolete. Andy Haldane said the possible disruption of what is known as the Fourth Industrial Revolution could be "on a much greater scale" than anything felt during the First Industrial Revolution of the Victorian era. He said that he had seen a widespread "hollowing out" of the jobs market, rising inequality, social tension and many people struggling to make a living. It was important to learn the "lessons of history", he argued, and ensure that people were given the training to take advantage of the new jobs that would become available. He added that in the past a safety net such as new welfare benefits had also been provided.

A large yet tidy refugee camp rises from the desert near the Syrian-Jordanian border. Most people wouldn't think of this as a hub of innovation, but nevertheless, a science and technology show has arrived with cameras and microphones. They're interviewing officials from UNICEF who describe the techniques they developed to safely remove sewage from the camp. Another week, and the cameras arrive in Stockholm to watch a new type of drone make its way through a dark tunnel. The show in question is 4Tech, a program on the BBC Arabic that since 2011 has attracted viewers in a market dominated by glitzy Arab versions of reality shows like "The Voice" and "Who Wants to Be a Millionaire."

The chief economist of the Bank of England has warned that the UK will need a skills revolution to avoid "large swathes" of people becoming "technologically unemployed" as artificial intelligence makes many jobs obsolete. Andy Haldane said the possible disruption of what is known as the Fourth Industrial Revolution could be "on a much greater scale" than anything felt during the First Industrial Revolution of the Victorian era. He said that he had seen a widespread "hollowing out" of the jobs market, rising inequality, social tension and many people struggling to make a living. He also argued that it was important to learn the "lessons of history" and ensure that people were given the training to take advantage of the new jobs that would become available. He said that in the past a safety net such as new welfare benefits had also been provided.

Toronto, Aug 19 (IANS) Dodgy lip sync dubbing could soon become a thing of the past as researchers have developed an Artificial Intelligence (AI)-based system that can edit the facial expressions of actors to accurately match dubbed voices. The system, called Deep Video Portraits, can also be used to correct gaze and head pose in video conferencing, and enables new possibilities for video post-production and visual effects, according to the research presented at the SIGGRAPH 2018 conference in Vancouver, Canada. "This technique could also be used for post-production in the film industry where computer graphics editing of faces is already widely used in today's feature films," said study co-author Christian Richardt from the University of Bath in Britain. The researchers believe that the new system could help the film industry save time and reduce post-production costs. Unlike previous methods that are focused on movements of the face interior only, Deep Video Portraits can also animate the whole face including eyes, eyebrows, and head position in videos, using controls known from computer graphics face animation.

An attendee looks at a Tifana.com Co. AI service character displayed on a screen at the Artificial Intelligence Exhibition & Conference in Tokyo, Japan, …

American History X director Tony Kaye is hoping to cast an artificial intelligence actor as the lead of his new film. According to Deadline, the British film-maker has made the unprecedented decision to employ a robot over a human for his next project, titled 2nd Born. The android will be trained in various techniques and a variety of acting methods and Kaye hopes it will lead to recognition by the Screen Actors Guild which could also lead to awards consideration. The idea is a joint effort from Kaye and producer Sam Khoze. The film is a sequel to comedy 1st Born starring Val Kilmer and Denise Richards, the first ever Iranian-American co-production.

The Terminator is a 1984 American science-fiction action film directed by James Cameron. It stars Arnold Schwarzenegger as the Terminator, a cyborg assassin sent back in time from 2029 to 1984 to kill Sarah Connor (Linda Hamilton), whose son will one day become a saviour against machines in a post-apocalyptic future. Michael Biehn plays Kyle Reese, a soldier from the future sent back in time to protect Connor. It received critical acclaim, with many praising its pacing, action scenes and Schwarzenegger's performance. Its success led to a franchise consisting of four sequels (Terminator 2: Judgment Day, Terminator 3: Rise of the Machines, Terminator Salvation and Terminator Genisys), a television series, comic books, novels and video games.

The goal of a recommender system is to show its users items that they will like. In forming its prediction, the recommender system tries to answer: "what would the rating be if we 'forced' the user to watch the movie?" This is a question about an intervention in the world, a causal question, and so traditional recommender systems are doing causal inference from observational data. This paper develops a causal inference approach to recommendation. Traditional recommenders are likely biased by unobserved confounders, variables that affect both the "treatment assignments" (which movies the users watch) and the "outcomes" (how they rate them). We develop the deconfounded recommender, a strategy to leverage classical recommendation models for causal predictions. The deconfounded recommender uses Poisson factorization on which movies users watched to infer latent confounders in the data; it then augments common recommendation models to correct for potential confounding bias. The deconfounded recommender improves recommendation and it enjoys stable performance against interventions on test sets.

Nefarious actors on social media and other platforms often spread rumors and falsehoods through images whose metadata (e.g., captions) have been modified to provide visual substantiation of the rumor/falsehood. This type of modification is referred to as image repurposing, in which often an unmanipulated image is published along with incorrect or manipulated metadata to serve the actor's ulterior motives. We present the Multimodal Entity Image Repurposing (MEIR) dataset, a substantially challenging dataset over that which has been previously available to support research into image repurposing detection. The new dataset includes location, person, and organization manipulations on real-world data sourced from Flickr. We also present a novel, end-to-end, deep multimodal learning model for assessing the integrity of an image by combining information extracted from the image with related information from a knowledge base. The proposed method is compared against state-of-the-art techniques on existing datasets as well as MEIR, where it outperforms existing methods across the board, with AUC improvement up to 0.23.