The actress best known for her role as a lovesick teenager in Twilight has co-authored a three-page paper on artificial intelligence. Kirsten Stewart, along with Adobe Research Engineer Bhautik Joshi and Starlight Studios Producer David Shapiro, released a paper Wednesday detailing how machine learning was applied to her directorial and screenwriting debut for the short film "Come Swim." The paper, titled "Bringing Impressionism to Life with Neural Style Transfer," explains how "neural style transfer" was used in the movie. In short, the "style transfer" can alter the style of a video in real time. For instance, had Stewart envisioned her film in the style of impressionist Claude Monet, she could have shown her algorithm a Monet work and taught the system to overlay the painting style on the film.

A heat-sensing film could let robots detect when humans are around, like pit vipers hunting out warm-blooded prey. The flexible, transparent coating is made of pectin, a low-cost plant material used to set jam. Unlike conventional electronics, it relies on currents of ions rather than electrons to detect temperature variations – just like natural membranes used by the snakes. The film can sense temperature changes as small as 10 millikelvin, which is twice as sensitive as human skin. It can detect a warm body the size of a rabbit from a metre away, something the researchers tested by microwaving a teddy bear and setting it at different distances from the film.

Artificial intelligence (AI) is all around us. Unlike the Terminator robots, AI exists in subtle ways, embedded in our daily activities thanks to the rise of big data and machine learning. When Facebook tries to connect users with new friends or businesses, Netflix suggests a new TV series to watch, or Amazon recommends a book, these are all examples of AI presented to people via machine learning – a statistical method that finds patterns and makes predictions based on vast volumes of data. After years of hype, most organisations now have a solid understanding of the potential of big data. In fact, the majority of them are actively pursuing means to capitalise on all the information they capture.

PARIS Just as IBM's Deep Blue showed the world a computer can play chess as well as a human master, Eduardo Reck Miranda, a researcher for the Sony Computer Science Laboratories Inc., aims to demonstrate a computer program able to compose original music. So far, neural networks have succeeded in imitating distinct musical styles, but truly original compositions have remained elusive. Miranda is tackling that problem with an orchestra of virtual musicians called agents that interact to compose original music. "From the viewpoint of a composer, I can hardly say that our agents are composing music at this stage," Miranda acknowledged. Instead, he said, "the breakthrough in this work is the action of collective machine learning for generative music systems."

Here's a sentence you don't get to read everyday: Kristen Stewart has surprised the artificial intelligence community by publishing a paper on machine learning. The Twilight actress recently made her directorial debut with the short film Come Swim, and in it used a machine learning technique known as "style transfer" (where the aesthetics of one image or video is applied to another) to create an impressionistic visual style. Along with special effects engineer Bhautik J Joshi and producer David Shapiro, Stewart has co-authored a paper on this work in the film, publishing it in the popular online repository for non-peer reviewed work, arXiv. Once more: Kristen Stewart of Twilight fame directs movie; writes arXiv paper about using StyleNet during production https://t.co/NZ4I1yhQUN To be someone in Hollywood, you've got to put your ML papers on Arxiv and you better use TensorFlow... https://t.co/2Rcg1ccJ36 Kristen Stewart has coauthored a paper about applying neural nets to images.

In this week's news roundup for IT leaders, we bring you the latest in the ongoing debate about the impact of artificial intelligence on the future of jobs. This week, The World Economic Forum took place in Switzerland, where political and economic leaders along with executives from companies including IBM, Microsoft, Facebook and Google parent Alphabet gathered to discuss the impact of automation and artificial intelligence on the future of jobs and society. Speaking at the event, Google co-founder Sergey Brin said that the growth of AI has surprised him, but he's optimistic overall. As Adam Satariano reports for the Chicago Tribune, Brin said that automation would ultimately free up people to work on more intellectually demanding, creative or artistic pursuits while AI took care of the mundane tasks. In a Wall Street Journal recap of the event, Sam Schechner reports that while many executives and economists share an optimistic viewpoint, "some said this week that they also worry the spoils of the next revolution could be inequitably shared – and that the transition to new models of work could be brutal for many workers."

After the US Presidential Election, many were furious at Facebook for helping to spread fake news. People were sharing stories that had little or no basis in reality, fuelling concerns that many votes were based on false beliefs. There was also the concern that it could lead to potentially violent incidents, as did happen. To combat the spread of fake news, it was recently revealed that Facebook would be using AI to help clamp down on illegitimate sources of news. Let's examine what this means. The US Election season sees a flurry of articles, all of it drenched in intense emotional responses due to the stakes involved.

Artificial Intelligence (AI) is the branch of computer sciences that emphasizes the development of intelligence machines, thinking and working like humans. Today, Artificial Intelligence is a very popular subject that is widely discussed in the technology and business circles. Many experts and industry analysts argue that AI or machine learning is the future -- but if we look around, we are convinced that it's not the future -- it is the present. With the advancement in technology, we are already connected to AI in one way or the other -- whether it is Siri, Watson or Alexa. Yes, the technology is in its initial phase and more and more companies are investing resources in machine learning, indicating a robust growth in AI products and apps in the near future.

While still a vast field, a huge part of machine learning exists for what may seem to be a relatively narrow subset of problems. These are problems involving visual processing: character recognition, facial recognition, the generation of trippy images dominated by populations of dogslugs, birdlegs, and spidereyes. Image data is unique in its suitability for machine learning tasks. It naturally occurs as multidimensional arrays--tensors, really--of pixel data. It's more at the fringes of machine learning that audio data gets a turn. Part of the problem is that, despite the vast amounts of digital audio data that exists in the world, there is a relative lack of openly accessible computational datasets.

Quartz, the business news site owned by Atlantic Media, gives away its global economics coverage to anyone who wants to click. It says it attracts about 20 million visitors a month. Now, Quartz is getting ready to charge money for some of its stuff: While the main site will remain free, Quartz is working on a subscription product, says Editor in Chief Kevin Delaney. Delaney won't go into details about what that product is, how much it will cost or when it will launch. But Quartz has given a hint by announcing the purchase of Intelligentsia.ai,