If you're already resentful of online dating culture and how it turned finding companionship into a game, you may not be quite ready for this: Crown, a new dating app that actually turns getting matches into a game. Crown is the latest project to launch from Match Group, the operator of a number of dating sites and apps including Match, Tinder, Plenty of Fish, OK Cupid, and others. The app was thought up by Match Product Manager Patricia Parker, who understands first-hand both the challenges and the benefits of online dating – Parker met her husband online, so has direct experience in the world of online dating. Crown won Match Group's internal "ideathon," and was then developed in-house by a team of millennial women, with a goal of serving women's needs in particular. The main problem Crown is trying to solve is the cognitive overload of using dating apps.

The dominant, state-of-the-art collaborative filtering (CF) methods today mainly comprises neural models. In these models, deep neural networks, e.g.., multi-layered perceptrons (MLP), are often used to model nonlinear relationships between user and item representations. As opposed to shallow models (e.g., factorization-based models), deep models generally provide a greater extent of expressiveness, albeit at the expense of impaired/restricted information flow. Consequently, the performance of most neural CF models plateaus at 3-4 layers, with performance stagnating or even degrading when increasing the model depth. As such, the question of how to train really deep networks in the context of CF remains unclear. To this end, this paper proposes a new technique that enables training neural CF models all the way up to 20 layers and beyond. Our proposed approach utilizes a new hierarchical self-attention mechanism that learns introspective intra-feature similarity across all the hidden layers of a standard MLP model. All in all, our proposed architecture, SA-NCF (Self-Attentive Neural Collaborative Filtering) is a densely connected self-matching model that can be trained up to 24 layers without plateau-ing, achieving wide performance margins against its competitors. On several popular benchmark datasets, our proposed architecture achieves up to an absolute improvement of 23%-58% and 1.3x to 2.8x fold improvement in terms of nDCG@10 and Hit Ratio (HR@10) scores over several strong neural CF baselines.

But in the last few years, Alexa and Siri have moved in. With this invasion of AI assistants comes incredible command over technology: Don't set a timer or check the weather; ask. And don't spring for that spinning, oak coffee-table caddy to house your obnoxious array of remotes. With the latest TV innovations, all you'll need to say is "Alexa, play'Dawson's Creek'" to immediately power on your TV, streaming device and soundbar, search for the show (now on Hulu), and start where it you left off. "The control and convenience that comes from the next generation of voice is really going to enhance the TV experience," said John Taylor, senior vice president of LG Electronics and friend of Eugene Polley and Dr. Robert Adler, engineers who invented Zenith's original 1950 remote.

Jefferson Graham tells why the Sony RX10IV is his favorite all-around camera on TalkingTech. Father's Day is almost here again, and if dad is a gear head, he'd love nothing more than new tech as his Sunday present. I'm part of that cliche, but if you're thinking of buying me something, I probably already have it. I can't wait for holidays to add to my collection. But I do have several ideas for the father in your life.

MICROSOFT HAS PATCHED a flaw in its Cortana virtual assistant that could enable hackers to bypass the lock screen on Windows 10 machines. The fix included in Microsoft's latest Patch Tuesday bug fix bundle, which comprises 12 updates intended to patch a total of 49 security vulnerabilities. This includes fixes for flaws in Windows, Office, SharePoint, and the Internet Explorer and Edge web browsers, along with a patch for the so-called'elevation of privilege vulnerability' in Microsoft's AI helper. Lane Thames, a senior security researcher at Tripwire, spoke out about the long-standing flaw with Cortana, that meant the AI helper was always listening for commands, even when a PC is locked. "The advisory states that'Cortana retrieves data from user input services without consideration for status'," said Thames.

Dating apps make a lot of money (exhibit a...see above) but it's not all cash registers and harmony at match group and pals. The young folks it seems are spending too much time on their phones and getting bored according to the Techcrunch exclusive. Create a new app called'Crown' and further gamify love to solve this. You can find love faster if you cut down options and increase competition. Sounds like a classy move. This just shows your original product blows...it's not cognitive overload.

SEO is one of the most fast-paced industries out there; constantly kept on our toes, it's one of the reasons we love it so much. But thinking about what the future holds for the industry can be both exciting and a little frightening. Will artificial intelligence (AI) ultimately make search better or worse? And what are the ramifications for SEOs? Plenty of questions and speculation abound.

Not all AI is created equal. Siri can find, book and calendar local movie tickets in minutes. Alexa or Google Assistant can turn up the thermostat automatically and order you a sweater when the weather gets cold. Virtual assistants are ever-present and increasingly capable and people have quickly adjusted to these types of interactions. By contrast, most enterprise chatbots essentially consist of a hovering box on a webpage -- an experience that pales in comparison to the norm consumers are used to. Floating boxes have their place, but they're quickly becoming only a small part of a bigger picture.

Language Technologies Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA A major challenge in recommender systems is handling new users, whom are also called cold-start users. In this paper, we propose a novel approach for learning an optimal series of questions with which to interview cold-start users for movie recommender systems. We propose learning interview questions using Deep Q Networks to create user profiles to make better recommendations to cold-start users. While our proposed system is trained using a movie recommender system, our Deep Q Network model should generalize across various types of recommender systems.

Amazon has begun shipping its delayed DeepLens, a $250 AI-powered camera which is designed to put machine learning capabilities into the hands of every software developer. Announced back in November 2017, the camera's full name is the Amazon Web Services DeepLens AI Deep Learning Video Camera. Picking that name apart, it is a camera which hooks up to Amazon's AWS web service and lets developers try their hand at creating apps which use machine learning. Amazon says it is the first video camera designed to teach developers the basics of deep learning, and to do this is comes with six sample projects to get you started. These include object detection, a system for correctly identifying cats and dogs, activity detection and face detection.