Amazon.com Inc. AMZN 1.24% introduced its Alexa digital assistant seven months after Cortana's launch, but its Echo and sibling devices now control two-thirds of the U.S. smart-speaker market, according to research firm eMarketer. The market share of devices using Cortana isn't large enough to be listed in eMarketer's tally. Microsoft's effort to turn Cortana into a viable competitor, while voice computing is still in its early days, is bigger than just the market for smart speakers that sit on kitchen counters checking the weather. It is an opportunity to lead in the next big advance in computing, in which people use their voices rather than a keyboard and mouse. Companies that master so-called conversational computing will have an edge in the emerging business just as Windows gave Microsoft an advantage in the PC era, analysts say.

For consumers, AI is already available in the form of wearable IoT devices, smart home speakers like Amazon Echo and Google Home, and personal digital assistants like Siri, Cortana, and Google Now. These gadgets are already being sold as products, but it's not a stretch to envision them becoming sold as services on a monthly payment model, which would conceivably include regular software updates and functionality improvements.

Artificial intelligence (AI) is increasingly getting attention from enterprise decision makers. Given that, it's no surprise that AI use cases are growing. According research conducted by Gartner, smart machines will achieve mainstream adoption by 2021, with 30 percent of large companies using AI. These technologies, which can take the form of cognitive computing, machine learning and deep learning, are now tapping advanced capabilities such as image recognition, speech recognition, the use of smart agents, and predictive analytics to reinvent the way organizations do business. Combined with other digital technologies, including the Internet of Things (IoT), a new era of AI promises to transform business.

Time magazine recently wrote that Artificial Intelligence "is one of the hottest, least understood and most debated tech breakthroughs in modern times." You can understand why too. On one hand, AI is already a part of our daily lives in ways we might not even be aware of (think digital assistants like Apple Siri or Google Assistant, sensor data in cars to assist with driving and parking, traffic cameras, etc.) On the other hand, we've been watching sci-fi movies our whole lives where robots always conquer humanity. Gallop recently found that 73% of Americans expect the increased use of AI will eliminate more jobs than it creates, while 63% predict that new tech and smart machines will widen the gap between rich and poor. Is it any surprise then that the future of AI would be a little intimidating?

The logo for the Tinder app, seen on a mobile phone screen in London in November 2016. The logo for the Tinder app, seen on a mobile phone screen in London in November 2016. Tinder's co-founders, along with eight other current and former executives, have slapped the popular dating app's owners with a massive lawsuit. In the suit filed Tuesday in New York, the Tinder employees past and present say the companies that own the app deliberately undervalued it to swindle them out of the money they were owed. And that is no small sum, according to founders Sean Rad, Justin Mateen, Jonathan Badeen and their fellow plaintiffs.

Conversational agents could provide timely and cost-effective social support to promote behavioral changes and improve healthcare outcomes. The authors evaluated the performance of their social media-based conversational agent in a smoking cessation program. Results showed that the presence of a conversational agent effectively increased participant engagement and enhanced their smoking cessation outcomes.

From self-driving vehicles and back-flipping robots to virtual assistants who book our next appointment at the hair salon or at that restaurant for dinner - machine learning systems are becoming increasingly ubiquitous. The main reason for this is that these methods boast remarkable predictive capabilities. However, most of these models remain black boxes, meaning that it is very challenging for humans to follow and understand their intricate inner workings. Consequently, interpretability has suffered under this ever-increasing complexity of machine learning models. Especially with regards to new regulations, such as the General Data Protection Regulation (GDPR), the necessity for plausibility and verifiability of predictions made by these black boxes is indispensable. Driven by the needs of industry and practice, the research community has recognised this interpretability problem and focussed on developing a growing number of so-called explanation methods over the past few years. These methods explain individual predictions made by black box machine learning models and help to recover some of the lost interpretability. With the proliferation of these explanation methods, it is, however, often unclear, which explanation method offers a higher explanation quality, or is generally better-suited for the situation at hand. In this thesis, we thus propose an axiomatic framework, which allows comparing the quality of different explanation methods amongst each other. Through experimental validation, we find that the developed framework is useful to assess the explanation quality of different explanation methods and reach conclusions that are consistent with independent research.

Dey et al. (2017), bayesian formulation of this problem is discussed. Hyper prameter choice was the major issue in that paper. However this problem was attempted only after suitable choice of feature dimension for user and movie feature vector. Usual method used to select such feature dimension is nothing but one dimensional grid search that select the dimension which minimizes the test error. This approach is boring as it attracts extra computational burden to select the feature dimension.

Pandora's Plus and ad-supported users have been able to listen using Google Home for almost two years, and the streaming service is now meshing more tightly with Google Assistant. Starting today, Premium listeners can use their voice to play on-demand tunes and playlists on devices with the assistant baked in, including Google's smart speakers and third-party devices. Listeners can set Pandora as their default music streaming service on Google Home, so you won't need to add the "on Pandora" caveat when you want to play something. If you're not quite sure what a song's called but know some of the lyrics, you can ask Google Assistant to track down the tune for you -- that's a feature Spotify doesn't have. Using your voice, you can also give a song a thumbs up or thumbs down, repeat a track, skip tunes and create stations.

What parent wouldn't use anything at their disposal to help their kids succeed? We know that sitting down with our kids and helping them grasp the concepts they're learning at school is the best way to help them academically. And they probably don't need more time interacting with electronics, but Alexa offers some skills that can help students when parents aren't available. Luckily, if you have an Amazon Echo smart speaker, (in this case we recommend the Echo Dot for Kids) you have access to a wealth of brain-sharpening, knowledge-enhancing activities. To enable a skill on your Echo device, just say, "Alexa, enable [exact name of skill]."