Smart assistants could come with a'moral AI' to decide whether to report their owners for breaking the law. That's the suggestion by academics at the University of Bergen, Norway, who touted the idea at the ACM conference on Artificial Intelligence, Ethics and Society in Hawaii. They suggest that domestic bots such as Amazon Echo and Google Home should be enhanced with moral AI. This would enable them to weigh-up whether to report illegal activity to the police, effectively putting millions of people under constant surveillance. Marija Slavkovik, Associate Professor the Department of Information Science and Media Studies, led the research behind the idea.

When Samsung launched its Bixby digital assistant with the Galaxy S8, some basic features were missing, and they were slow to arrive. On top of that, Bixby was installed alongside the well-established Google Assistant, prompting questions as to whether it was really necessary to add another digital assistant to an already crowded market. Samsung may have realized Bixby's shortcomings as a digital assistant, but with Bixby 2.0 the Korean tech giant is hardly backing down. Bixby 2.0 is the lead element of Samsung's bid to build its own ecosystem of connected devices and services. The new Bixby strategy is vastly different from what came before it, which is why we've chosen to publish this article to accompany our original Bixby cheat sheet, which focuses more on its digital assistant features.

With multiple facets to optimise for higher conversions, ecommerce brands often treat on-site search as an afterthought. By failing to address the search experience, you are losing customers, especially when you consider that shoppers who use the on-site search bar reportedly have a higher conversion rate and average order value. Machine learning may be hyped technology but it's already making a major difference to the on-site product search experience. Here are three examples demonstrating how progressive ecommerce brands are succeeding with it. Commonly misspelt words are a lost revenue opportunity for ecommerce companies.

If a smart home detects the unmistakable whiff of cannabis smoke in a teenager's bedroom, should it tell their parents? Situations like this are on the horizon with digital assistants, like Amazon Echo or Google Home, making it into many people's homes. One proposal for reaching resolutions is that a handful of artificially intelligent bots should debate the possibilities before reaching a decision.

Have you ever dived into that imaginative soul of yours wondering how dating will be like in the years to come? The way people meet, converse and form connections with each other is forever changing. With the rise of technology, digital courtship among individuals has massively changed. If you compare the present digitalised generation with its previous, you will realise that technology has played a massive role in shaping the path of online dating. Presently, studies have shown that most 18 to 30-year olds are the ones that use online dating services and apps.

We present a large scale hyperbolic recommender system. We discuss why hyperbolic geometry is a more suitable underlying geometry for many recommendation systems and cover the fundamental milestones and insights that we have gained from its development. In doing so, we demonstrate the viability of hyperbolic geometry for recommender systems, showing that they significantly outperform Euclidean models on datasets with the properties of complex networks. Key to the success of our approach are the novel choice of underlying hyperbolic model and the use of the Einstein midpoint to define an asymmetric recommender system in hyperbolic space. These choices allow us to scale to millions of users and hundreds of thousands of items.

Understanding temporal dynamics has proved to be highly valuable for accurate recommendation. Sequential recommenders have been successful in modeling the dynamics of users and items over time. However, while different model architectures excel at capturing various temporal ranges or dynamics, distinct application contexts require adapting to diverse behaviors. In this paper we examine how to build a model that can make use of different temporal ranges and dynamics depending on the request context. We begin with the analysis of an anonymized Youtube dataset comprising millions of user sequences. We quantify the degree of long-range dependence in these sequences and demonstrate that both short-term and long-term dependent behavioral patterns co-exist. We then propose a neural Multi-temporal-range Mixture Model (M3) as a tailored solution to deal with both short-term and long-term dependencies. Our approach employs a mixture of models, each with a different temporal range. These models are combined by a learned gating mechanism capable of exerting different model combinations given different contextual information. In empirical evaluations on a public dataset and our own anonymized YouTube dataset, M3 consistently outperforms state-of-the-art sequential recommendation methods.

Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you'd talk to another person. The hard part is getting your machine to understand and talk back to you like it's that other person. Today, Dr. El Asri talks about the particular challenges she and other scientists face in building sophisticated dialogue systems that lay the foundation for talking machines. She also explains how reinforcement learning, in the form of a text game generator called TextWorld, is helping us get there, and relates a fascinating story from more than fifty years ago that reveals some of the safeguards necessary to ensure that when we design machines specifically to pass the Turing test, we design them in an ethical and responsible way. Layla El Asri: In a video game, most of the time you only have a few actions that you can take. You just need to learn when you should go right, when you should go left, when you should go up, when you should go down. But when it comes to dialogue, you need to learn how to make a sentence that is grammatically correct, and then you need to learn how to make a sentence that makes sense in the global context of the dialogue, or a sentence that brings new information in the dialogue that is going to make the person you are talking to satisfied with the sentence. Your action space is just huge because it's not just up/down, right/left, it's all the sentences you could imagine! Host: You're listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. Host: Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you'd talk to another person.

Armani Beauty unveiled its first dedicated pop-up in West Hollywood earlier this month, celebrating its unveiling with a roster of celebrities, including Dakota Fanning and Katherine Schwarzenegger, and a handful of product exclusives. The all-red 2,000-square-foot Armani Box is so far the only place in the U.S. to have the brand's new Power Fabric High Coverage Stretchable Concealer and the Foundation Balm, which will roll out nationally in March. Also, there's a vending machine on hand that delivers take-home samples as well as other technology such as mirrors that show the shopper what a particular lip color will look like on the person. Tim Quinn, Giorgio Armani Beauty celebrity makeup artist, said the Melrose Place location was "an iconic spot for someone to discover" and that although the offering was "soup to nuts, skin care through fragrance," the pop-up has a focused and curated feel. "The brand is known for foundation," said Quinn, adding that he often recommends his clients have three different foundations -- one each for weekends, evenings and workdays.

Graduates are to be given the chance to become qualified experts in Artificial Intelligence through a new set of masters courses and work-based placements. The move aims to drive up skills in the AI sector with courses and placement being funded by Google's Deepmind and British security and defence giant BAE Systems. This research for Doctoral Training will be made available over five years as part of the scheme. Graduates are to be given the chance to become qualified experts in artificial intelligence (AI) through a new set of masters courses and work-based placements. Advances in modern computing technologies have created an explosion of major breakthroughs in the field of Artificial Intelligence.