Max Kalmykov is the VP of Media and Entertainment at DataArt. Broadcasters and movie studios alike are starting to explore the huge potential of modern technologies to bring a new generation of filmed entertainment to our TV sets and cinemas. Artificial intelligence, machine learning, and deep learning are the buzzwords that excite video executives with promises of revolutionary new abilities for video creation and editing. Deep learning, in particular, is the new frontier for the video industry, allowing video professional to do things automatically that would have taken weeks of work in the past, as well as some things that wouldn't have been possible at all. How is deep learning different from other machine learning algorithms?

The destruction of reality just got one step closer with a new Artificial Intelligence development that will help the world sink further into discord, unrest, and good old propaganda: a neural network capable of writing believable fake comments to news articles. DeepCom -- as the new horseman of the AI apocalypse is called -- has recently been made public in a research paper by engineers from Microsoft and Beihang University in China. According to the paper, the scientists believe that "automatic news comment generation is beneficial for real applications." The system is formed by two neural networks: one to analyze the content of the article -- which interprets the headline, lede and body to realize what are the important points. Then, another neural network uses that information to generate the fake comment.

This document describes the proposal to "add traditional Machine Learning algorithms to the Swift TensorFlow library", for "TensorFlow" organization.

The most prolific musical artists manage to release one, maybe two, studio albums in a year. Rappers can sometimes put out three or four mixtapes during that same time. However, Auxuman plans to put out a new full-length album, featuring hot up-and-coming artists like Yona, Mony, Gemini, Hexe, and Zoya, every single month. Before this goes any further, don't worry: You're not hopelessly out of touch with today's pop music. Well, at least not in the sense that you could meet them and shake their hands.

As portrayed so aptly in the Netflix documentary The Great Hack that shed light on Cambridge Analytica's Facebook data scandal, there are rising concerns around how users' data is leveraged for political and commercial gain. With the growth of artificial intelligence or AI, technology will play an even greater role in our lives. AI will significantly change not only the type of work performed in many professions but also the roles themselves over the coming years. But what about the ethical challenges that AI also bring? If AI is used for simulation of human intelligence processes, what role do professionals have as ethical guardians in the work they do?

At the corner of the canvas, a mathematical equation ostentatiously replaced the traditional artist signature.

Propaganda aims at influencing people's mindset with the purpose of advancing a specific agenda. Previous work has addressed propaganda detection at the document level, typically labelling all articles from a propagandistic news outlet as propaganda. Such noisy gold labels inevitably affect the quality of any learning system trained on them. A further issue with most existing systems is the lack of explainability. To overcome these limitations, we propose a novel task: performing fine-grained analysis of texts by detecting all fragments that contain propaganda techniques as well as their type. In particular, we create a corpus of news articles manually annotated at the fragment level with eighteen propaganda techniques and we propose a suitable evaluation measure. We further design a novel multi-granularity neural network, and we show that it outperforms several strong BERT-based baselines.

It's a tool that uses machine learning to guide content creators through the writing process.

Artificial intelligence generated writing and similar tools are offering journalists a second chance to reconnect with the public and up-their-game, according to Charlie Becket. The researcher is director of the Media Policy Project, sponsored by the London School of Economics and Political Science. "AI in its broadest sense provides all sorts of opportunities for journalism – and journalism needs all the help it can get right now," Beckett says. The reason: "A few years ago, a couple of companies said they would be able to replace journalists within a few years, Van der Lee, says. It's a boast that turned out to be untrue. Instead, AI systems like Van der Lee's – which can generate short sports stories, which detail results of thousands of local soccer matches on a regular basis – are all about doing rote work. That frees-up journalists to write more complex, more insightful news stories and features, according to Van der Lee. "Robots will never write as well as people," Van der Lee says. It's an AI editor that works in popular Web browsers. The new feature on the AI editing tool can offer suggestions to create a writing tone that is neutral, confident, joyful, optimistic, friendly, urgent, analytical or respectful. Currently, Grammarly's tone analysis is available for Google Chrome users only. The toolmaker's plan in coming months is to roll-out the feature to Firefox, Safari and other popular browsers. It's a step-by-step guide on how to get started using AI-generated writing for public relations, marketing and similar endeavors in content generation. "Today, instead of three-to-five hours, reports take us 10 minutes to write," Moehring says. "The reports are delivered on the first business day of the month.