Sling TV is introducing an arguably overdue feature for insatiable viewers: personalized recommendations. As of January 17th, Apple TV users will receive custom-tailored suggestions for live and on-demand programs, whether it's a channel, a movie or a sports match. You can find it in the My TV section in a carousel alongside favorites. The show advice will be coming to other devices "in the future," and there are plans for both improved recommendations as well as more personalization going forward. The addition isn't a shock when rivals like YouTube TV have had recommendations, but it'll be a bit help if you like Sling TV's experience.

And even these engagement patterns are giving way to new and more seamless and natural methods of interaction. For example, images and video feeds can be used to track assets, authenticate individual identities, and understand context from surrounding environments. Advanced voice capabilities allow interaction with complex systems in natural, nuanced conversations. Moreover, by intuiting human gestures, head movements, and gazes, AI-based systems can respond to nonverbal user commands. Intelligent interfaces combine the latest in human-centered design techniques with leading-edge technologies such as computer vision, conversational voice, auditory analytics, and advanced augmented reality and virtual reality. Working in concert, these techniques and capabilities are transforming the way we engage with machines, data, and each other. At a dinner party, your spouse, across the table, raises an eyebrow ever so slightly. The gesture is so subtle that no one else notices, but you received the message loud and clear: "I'm bored. Most people recognize this kind of intuitive communication as a shared language that develops over time among people in intimate relationships. We accept it as perfectly natural--but only between humans.

I recently discovered it's possible for someone in their 20s to feel old--just mention Microsoft's Clippy to anyone born after the late 90s. Weirdly, there is an entire generation of people who never experienced that dancing wide-eyed paper-clip interrupting a Word doc writing project. For readers who never knew him, Clippy was an interactive virtual assistant that took the form of an animated paperclip designed to be helpful in guiding users through Microsoft Word. As an iconic symbol of its decade, Clippy was also famously terrible. Worldwide consensus decided that Clippy was annoying, intrusive, and Time magazine even named it among the 50 worst inventions of all time (squeezed between'New Coke' and Agent Orange.

This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. This course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization.

The Amazon Echo lineup has long been a popular pick for making homes a little smarter, and the Echo Dot Kids Edition brings those same smarts to the littlest members of your household. Today, you can snag the Echo Dot Kids Edition for $40 on Amazon, down from a list price of $70 and the lowest we've seen it. This compact smart speaker comes with Alexa built in for convenient voice control. Kids can do everything from controlling other connected devices to asking Alexa to answer questions and tell stories hands-free. With one year of included Amazon's FreeTime service included with your purchase, kids will be able to tap into a whole library of family-friendly content.

As fintech disruptors change how everything works, banks and financial institutions are either partnering with them or developing and deploying their own solutions. With the world becoming one enormous marketplace, we have seen a constant change in how businesses take place. This has been further fueled by new technologies and rapidly evolving customer expectations. Even the highly regulated banking and finance sector has in recent times witnessed the constant metamorphosis of its business models to stay ahead in disruptive times. When it comes to the financial services ecosystem, the fintech industry plays a significant role in determining how the sector moves forward.

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since Amazon Echo shipped in late 2014, smart speakers and voice assistants have been advertised as the next big thing. Nearly four years later, despite the millions of devices sold, it's clear that like many other visions of the tech industry, that perception was an overstatement. Testament to the fact: Most people aren't using Alexa to make purchases, one of the main advertised use cases of Amazon's AI-powered voice assistant. Voice assistants have existed before the Echo.

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. The past few years, smart home technology has grown drastically in popularity, which means more smart devices are being sold at incredibly affordable prices. These gadgets can help with small everyday problems, acting as a personal assistant, helping you stream your favorite media, and assisting with cooking perfectly. You don't even have to spend too much.

Playlist recommendation involves producing a set of songs that a user might enjoy. We investigate this problem in three cold-start scenarios: (i) cold playlists, where we recommend songs to form new personalised playlists for an existing user; (ii) cold users, where we recommend songs to form new playlists for a new user; and (iii) cold songs, where we recommend newly released songs to extend users' existing playlists. We propose a flexible multitask learning method to deal with all three settings. The method learns from user-curated playlists, and encourages songs in a playlist to be ranked higher than those that are not by minimising a bipartite ranking loss. Inspired by an equivalence between bipartite ranking and binary classification, we show how one can efficiently approximate an optimal solution of the multitask learning objective by minimising a classification loss. Empirical results on two real playlist datasets show the proposed approach has good performance for cold-start playlist recommendation.

Google's aptly named AI helper, Google Assistant, is poised to have a great year in 2019. Not only will the digital assistant be spreading to numerous devices old and new, but there are a host of new features coming, too, several of which were shown off at CES 2019 last week. This list of upcoming Google Assistant updates is long, and it can be overwhelming trying to parse out all the different announcements and keep track of when these new features will finally be available. To help, we've curated a rundown detailing the best and most important updates coming for Google Assistant in the next few months, including what devices these new features have been announced for, their expected release dates, and how to enable them (when available). By far, the most hyped new Assistant feature at CES was the Interpreter Mode.