There are further Assistant updates regardless of how connected your home might be. Actions now include more advanced media playback for formats beyond music and podcasts. You can listen to clips from TV shows or a white noise generator, for instance, and get control over it like you would any other media format. You can also subscribe to daily updates and other notifications on your phone if you always want the latest news, and there's now a browsing carousel when you have a plethora of visual choices (clearly, this only works on screen-equipped devices). While all these updates are helpful, Custom Device Actions may hold the most potential.

Advanced topic extraction using AI & machine learning, natural language processing, and regex classifiers to identify topics across all data sources - enabling organizations to diagnose not only what is happening in customer interactions, but why it's happening. Sentiment analysis and entity recognition using proprietary and open source algorithms to understand the overall sentiment and label data by types such as person, organization, location, events, and products. Pre-configured industry dashboards and classifier libraries that address the most common uses cases for sales, churn and compliance to jumpstart time-to-value. Data connectors to a variety of data sources and destinations, send classified data to an internal visualization tool or build powerful apps using the ListenLogic API. On premise or cloud deployment leveraging proprietary data redaction that removes personally identifiable information for an added level of security.

March Madness is coming--here's what you need to binge watch the games (Photo: Jamie Squire/Rainer Puster/Getty Images) If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. For sports fans, the most wonderful/unproductive time of the year has arrived. The first weekend of March Madness, the all-day basketball bonanza that runs from early afternoon to late night from Thursday to Sunday, is my happy place. Other than opening day in baseball, it's my favorite time to watch sports all year.

CIOs are developing "a sort of tunnel vision about AI," Isaac Sacolick, a former CIO who now advises CIOs on big initiatives like digital transformation, told me recently. Looking to establish accountability across disparate project teams? Trying to automate processes or allow for lean methodology support? Hoping to enable business consequence modeling or real-time reporting? If you answered'yes' to any of these questions, then you need to download this comprehensive, 68-page PDF guide on selecting, managing, and tracking IT projects for superior service delivery.

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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).