To stop spread of disinformation leading to widespread public disorder, the government is exploring use of Artificial Intelligence (AI) to remove such content automatically from social media platforms. The Centre is to "take up the issue with representatives of various international social media platforms operating in the country and monitor their compliance to instructions issued by lawful authorities under Information Technology Act." Sources said, "The introduction of Artificial Intelligence to remove objectionable content automatically from social media platforms needs to be explored." This step was proposed after the government witnessed widespread public disorder because of spread of rumours in mob lynching cases. The Ministry of Home Affairs has taken up the matter and is exploring ways to implement it. On the rise in sharing of fake news over social media platforms such as Facebook, Twitter and WhatsApp, Minister of Electronics and Information Technology Ravi Shankar Prasad had said in Lok Sabha that "With a borderless cyberspace coupled with the possibility of instant communication and anonymity, the potential for misuse of cyberspace and social media platforms for criminal activities is a global issue."

Three years ago, AI became a new selling point for smartphones. For a time, smartphones supporting AI features quickly spread, and AI performance has become the most important mobile processor parameter after the CPU and GPU. Today, demonstrating AI performance has become an indispensable part of mobile phone and mobile processor conferences. When it comes to the AI function on mobile phones, many people can immediately think of it-smart voice assistant and AI camera. There is no doubt that AI photography is the most commonly used function by ordinary consumers.

Knowledge bases (KBs), pragmatic collections of knowledge about notable entities, are an important asset in applications such as search, question answering and dialogue. Rooted in a long tradition in knowledge representation, all popular KBs only store positive information, while they abstain from taking any stance towards statements not contained in them. In this paper, we make the case for explicitly stating interesting statements which are not true. Negative statements would be important to overcome current limitations of question answering, yet due to their potential abundance, any effort towards compiling them needs a tight coupling with ranking. We introduce two approaches towards compiling negative statements. (i) In peer-based statistical inferences, we compare entities with highly related entities in order to derive potential negative statements, which we then rank using supervised and unsupervised features. (ii) In query-log-based text extraction, we use a pattern-based approach for harvesting search engine query logs. Experimental results show that both approaches hold promising and complementary potential. Along with this paper, we publish the first datasets on interesting negative information, containing over 1.1M statements for 100K popular Wikidata entities.

You can't teach an old dog new tricks but you may one day be able to train them with new technology. The little white box seen here is actually an artificial intelligence trainer for dogs. It's called "Companion" and right now it's for dog care facilities. The company, Companion Labs, says the device uses a video camera, computer and treats to teach dogs new tricks. It gives the pet a verbal order.

A guest post by Tencent QQ Music Audio Engineering Team Introduction QQ Music is a music streaming service owned by the Tencent Music Entertainment Group (TME) and we serve 800M users globally. We have a massive music library with an extensive collection of albums and live music available in both audio and video formats.

When artificial intelligence is fully operational, it will transform the media and marketing industries. In particular, I believe that synthetic personalities powered by AI will change the way we learn about new products and how to use them. In my previous article, I showed how the collapse of broadcast TV exposed a huge weakness in the advertising industry. And I pointed to the nascent field known as Influencer Media, and especially Virtual Influencers, as a harbinger of the future of engagement brand-building. What happens when artificial intelligence is available to any app, any advertising campaign, and any brand marketer? How will that change things? Here's my answer: the media landscape will be transformed so deeply that it will be completely unrecognizable. All the leftover junk from the 20th century will be kaputt, including one-size-fits-all video programs for mass audiences, appointment viewing of a TV schedule and the very concept of TV channels, and the outdated intrusion of interruption advertising. Personalized programming and fully-responsive adbots will be the new norm.

Sunspring debuted at the SCI-FI LONDON film festival in 2016. Set in a dystopian world with mass unemployment, the movie attracted many fans, with one viewer describing it as amusing but strange. But the most notable aspect of the film involves its creation: an artificial-intelligence (AI) bot wrote Sunspring's screenplay. "Maybe machines will replace human storytellers, just like self-driving cars could take over the roads." A closer look at Sunspring might raise some doubts, however.

Below I'm going to talk about two of the most used digital products and how they use AI and machine learning in order to provide the best user experience. So, before we dive into Google's wonder search platform, we have to clear something off, since there's a lot of confusion around this. Most of my friends call it Google suggestions, but it's not the case. Since they integrated AI and machine learning in their search algorithms, those are not suggestions anymore, but predictions. "What's the difference between those two?" you may ask.