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Alexa is starting to weird out Amazon Echo users with her laughter … because she's not laughing with you--she's laughing at you.

To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph as the source of side information. To address the limitations of existing embedding-based and path-based methods for knowledge-graph-aware recommendation, we propose Ripple Network, an end-to-end framework that naturally incorporates the knowledge graph into recommender systems. Similar to actual ripples propagating on the surface of water, Ripple Network stimulates the propagation of user preferences over the set of knowledge entities by automatically and iteratively extending a user's potential interests along links in the knowledge graph. The multiple "ripples" activated by a user's historically clicked items are thus superposed to form the preference distribution of the user with respect to a candidate item, which could be used for predicting the final clicking probability. Through extensive experiments on real-world datasets, we demonstrate that Ripple Network achieves substantial gains in a variety of scenarios, including movie, book and news recommendation, over several state-of-the-art baselines.

Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity. In many domains, the two processes are approached through rules: high-level principles that reveal invariances within similar yet diverse examples. Under a probabilistic setting for discrete input spaces, we focus on the rule realization problem which generates input sample distributions that follow the given rules. More ambitiously, we go beyond a mechanical realization that takes whatever is given, but instead ask for proactively selecting reasonable rules to realize. This goal is demanding in practice, since the initial rule set may not always be consistent and thus intelligent compromises are needed. We formulate both rule realization and selection as two strongly connected components within a single and symmetric bi-convex problem, and derive an efficient algorithm that works at large scale. Taking music compositional rules as the main example throughout the paper, we demonstrate our model's efficiency in not only music realization (composition) but also music interpretation and understanding (analysis).

This Friday marks the start of the fifth annual Atlanta Science Festival, kicking off with Rise Up, Robots, a variety show featuring an assortment of robotic performers. One of those performers will be Shimon, a marimba-playing robot that uses machine learning to develop new and inventive compositions. Shimon was created by Gil Weinberg, professor and founding director of Georgia Tech's Center for Music Technology. Many at Tech have heard of Shimon and its ability to improvise jazz melodies. This Friday, though, the musical robot will tread uncharted territory, showcasing a new rock composition composed by Zach Kondak, a graduate student in music technology, who will also play drums and guitar.

Streaming giant Netflix has pledged that it will never feature advertising on its site and has no intention of entering the battle for live news and sports broadcasting. "Our content is our crown jewel," said CEO Reed Hastings, speaking two days after the company won an Oscar for its Russian sports doping documentary Icarus and ahead of the release of the new series of Jessica Jones. "It's up to us to take [subscribers'] money and turn it into great content for their viewing benefit." Speaking at Netflix Labs Day, a rare press event at the company's headquarters in Los Gatos, California, Hastings stressed his opposition to "chopping up" the site's movies and TV shows to accommodate commercials. "Having a great experience... vastly outweighs the fact that one company is gaining a lot of influence," he said, alluding to Netflix's market dominance, now under renewed threat from rivals Amazon Prime, Hulu and Disney (bolstered by its recent multi-billion dollar takeover of Fox).

AI Incorporated, Canada's pioneering robotics and artificial intelligence research company, is working on a design for an autonomous refuse receptacle robot. A new application for mobile robotics, the new AI enhanced robotic system allows for a continuous cycle of mobile robotic devices to work in order to provide the end user with unending service. With this new application in mobile robotics, the company plans to use its Simultaneous Localization and Mapping (SLAM) technology combined with deep learning and to pioneer in a new generation of robots. The autonomous refuse receptacle robot is an application for the company's Versatile Self Localizing Autonomous Platforms (VSLAP). This new robot proprietary software called the Quantum Slam Operating System helps companies mobilize any given machine.

Over the course of the last few years, Artificial intelligence (AI) has become recognised as one of the keys to solving some of the world's most complex issues - unlocking a level of growth and innovation that has never been seen before. Governments across the globe are now shifting gear, actively designing investment approaches, invectives and discussing regulatory frameworks to help their nations maintain a top spot in this emerging industry. U.S. policy makers and industry are grappling with the challenge of regulating without stifling innovating and the AI opportunity was central focus earlier this year at Davos, as the UK Prime Minister outlined her commitment "to ensure it works for everyone – be that in people's jobs or their daily lives". For all the good that is being touted about AI, there are also some unsavoury reports on the effect AI could have on the current demographic of the workforce, far more imminent than the Hollywood narrative of'robots taking over the world' – if true this could rock women's hard fought and rightful place on the career ladder. This is demonstrated in recent research from PwC, which indicates that women's jobs could be affected by automation over the next decade – with potentially 23% of women's jobs at risk, around 7% more than men. At a crucial time when the world is discussing and designing the way that AI will change the way we work, the higher risk of displacement felt by certain members of society must be made more visible and addressed alongside the serious skills shortage we are seeing in the tech sector amongst women.

Business Finland has granted 678,000 euros to a team lead by Aalto University's Jussi Rintanen for the commercialisation of a new information system technology based on artificial intelligence. Rintanen wants not only to automate the development of large information systems but also to integrate all parts of software development into a single functioning whole. Information systems projects in health care and in public sector administration, for instance, are highly labour intensive. The whole information system market in Finland is worth about two billion euros annually, and worldwide the figure is about 200 billion. Information systems projects with overruns in time and costs, or projects that cannot be completed at all, suffer from the same basic problem: a massive amount of routine programming work whose management is extremely difficult.

Unanimous AI is known for accepting high-profile challenges from journalists, testing the power of its Swarm AI technology across a range of venues. After correctly predicting the World Series and Kentucky Derby -- and perfectly forecasting Trump's 100-day approval rating before he even took office -- Unanimous AI took aim at the 90th Academy Awards, publishing its prediction here at Inverse last week. Its Swarm AI technology was nearly perfect, achieving 94 percent accuracy across the 16 major award categories, with only one award not coming out as predicted. The technology was 100% percent accurate in forecasting winners in the six major categories, including Best Picture. In that category, Swarm AI disagreed with most industry experts – and the Vegas odds – all of which deemed Golden Globe winner Three Billboards Outside Ebbing, Missouri the favorite over Swarm AI's predicted winner, The Shape of Water.