Google has collaborated with Polis, the international journalism think-tank at London School of Economics and Political Science, to create "Journalism AI". This new AI technology wants to help journalists fight fake news. Journalism AI" project will focus on research and training for newsrooms. To help news industry use Artificial Intelligence (AI) in more innovative ways. Part of the Google News Initiative (GNI), the "Journalism AI" project will focus on research and training for newsrooms on the intersection of AI and journalism.

Interactions such as double negation in sentences and scene interactions in images are common forms of complex dependencies captured by state-of-the-art machine learning models. We propose Mah\'e, a novel approach to provide Model-agnostic hierarchical \'explanations of how powerful machine learning models, such as deep neural networks, capture these interactions as either dependent on or free of the context of data instances. Specifically, Mah\'e provides context-dependent explanations by a novel local interpretation algorithm that effectively captures any-order interactions, and obtains context-free explanations through generalizing context-dependent interactions to explain global behaviors. Experimental results show that Mah\'e obtains improved local interaction interpretations over state-of-the-art methods and successfully explains interactions that are context-free.

Classical supervised learning produces unreliable models when training and target distributions differ, with most existing solutions requiring samples from the target domain. We propose a proactive approach which learns a relationship in the training domain that will generalize to the target domain by incorporating prior knowledge of aspects of the data generating process that are expected to differ as expressed in a causal selection diagram. Specifically, we remove variables generated by unstable mechanisms from the joint factorization to yield the Graph Surgery Estimator---an interventional distribution that is invariant to the differences across domains. We prove that the surgery estimator finds stable relationships in strictly more scenarios than previous approaches which only consider conditional relationships, and demonstrate this in simulated experiments. We also evaluate on real world data for which the true causal diagram is unknown, performing competitively against entirely data-driven approaches.

Showbox, a mysterious app that allows people to watch new films and TV shows for free, is back after a strange outage. But the circumstances around that return is largely unknown, and anyone trying to use the popular app might be endangering themselves and their computer. Showbox is a hugely popular app that allows for a Netflix-like experience but includes apparently torrented versions of new movies and TV shows. More specifically, there appears to be a number of versions of the app, all of which present themselves as the legitimate app. The service stopped working recently, prompting concerns that the service might have been taken down entirely – but it seems to have emerged once again.

We report a data mining pipeline and subsequent analysis to understand the core periphery power structure created in three national newspapers in Bangladesh, as depicted by statements made by people appearing in news. Statements made by one actor about another actor can be considered a form of public conversation. Named entity recognition techniques can be used to create a temporal actor network from such conversations, which shows some unique structure, and reveals much room for improvement in news reporting and also the top actors' conversation preferences. Our results indicate there is a presence of cliquishness between powerful political leaders when it comes to their appearance in news. We also show how these cohesive cores form through the news articles, and how, over a decade, news cycles change the actors belonging in these groups.

Believe it or not- we all are leveraging artificial intelligence like technology in our everyday life.

Whether an artificial intelligence could replace a medical doctor is both a matter for future conjecture and a hotly contested subject.

Along with the usual highlights from this week, we have some space exploration highlights, including your first chance to hear the wind on Mars. Also, Ghost in the Shell: Stand Alone Complex_2045 is coming to Netflix, and you need to know about the Audi E-Tron. NASA's InSight lander picked up something that other Mars missions never have -- audio of the planet's winds. "Capturing this audio was an unplanned treat," Bruce Banerdt, InSight's principal investigator, said in a statement. "But one of the things our mission is dedicated to is measuring motion on Mars, and naturally that includes motion caused by sound waves."

Methods proposed in the literature towards continual deep learning typically operate in a task-based sequential learning setup. A sequence of tasks is learned, one at a time, with all data of current task available but not of previous or future tasks. Task boundaries and identities are known at all times. This setup, however, is rarely encountered in practical applications. Therefore we investigate how to transform continual learning to an online setup. We develop a system that keeps on learning over time in a streaming fashion, with data distributions gradually changing and without the notion of separate tasks. To this end, we build on the work on Memory Aware Synapses, and show how this method can be made online by providing a protocol to decide i) when to update the importance weights, ii) which data to use to update them, and iii) how to accumulate the importance weights at each update step. Experimental results show the validity of the approach in the context of two applications: (self-)supervised learning of a face recognition model by watching soap series and learning a robot to avoid collisions.

Earlier this week, the rapper 2 Milly filed a lawsuit claiming that Fortnite--the most popular video game in the world--swiped his dance move. The case fuels ongoing controversy over video game companies' unlicensed use of existing hip-hop dances, which players can purchase to customize their in-game avatars. But can these companies freely copy and sell dance moves without payment to the artist? The groove in question is the "Milly Rock," a simple, two-step dance in which the arms circle while the hips swing from side to side. Popularized by 2 Milly in 2014, it became a viral hip-hop phenomenon.