Makes me feel sad for the rest. Actually, that's a movie ("The Spy that Loved Me") that Netflix recommends for me since I'm a James Bond junkie and Netflix knows that. In fact, Netflix knows a lot about me as it knows a lot about all of its viewers, which is one reason why Netflix is a Wall Street darling and has rewarded its stockholders very well over the past couple of years (see Figure 1). But Netflix isn't doing anything that other organizations cannot do. To replicate Netflix's business success starts with thinking differently about the role of data and analytics in powering the organization's business.

Artificial Intelligence (AI) is the talk of the world and it features prominently in predictions for 2019 (see here and here) and recent surveys by consulting firms and other observers of the tech scene. Consumer adoption: "Smart speakers" lead the way to the AI-infused home of the future Smart speakers (e.g., Amazon Echo and Google Home) will become the fastest-growing connected device category in history, with an installed base projected to surpass 250 million units by the end of 2019. With sales of 164 million units at an average selling price of $43 per unit, total smart speakers' revenues will reach $7 billion, up 63% from 2018. In 2019, among companies using AI, 70% will obtain AI capabilities through the cloud. Cloud-based AI software and services will make it easier for companies to benefit from AI, accelerating their adoption and spreading their benefits.

Listen up, Apple Music subscribers--HomePod isn't the only smart speaker that can handle your tunes anymore. Apple has teamed up with Amazon to allow streaming on Echo devices, so all of your songs, albums, and playlists are good to go. Here's how to set it all up: Setting up Apple Music on your Echo device takes just a few taps. Now you can say, "Alexa, play'Imagine' by Ariana Grande on Apple Music" and it'll start playing. You can also ask Alexa to stream playlists, charts, and Beats 1 radio.

The Amazon Echo Wall Clock is finally available. First announced back in September, the analog clock that can sync with timers and display countdowns set through Alexa sells for $30. To get the most of this wall clock, you'll need an Echo speaker to pair with it. The clock itself doesn't have a microphone so you'll have to issue commands via a connected Alexa device. Amazon's 10-inch, AA-powered wall clock looks pretty basic with its modern minimalist design, but the device has 60 LEDs that display information.

Recently multi-domain recommender systems have received much attention from researchers because they can solve cold-start problem as well as support for cross-selling. However, when applying into multi-domain items, although algorithms specifically addressing a single domain have many difficulties in capturing the specific characteristics of each domain, multi-domain algorithms have less opportunity to obtain similar features among domains. Because both similarities and differences exist among domains, multi-domain models must capture both to achieve good performance. Other studies of multi-domain systems merely transfer knowledge from the source domain to the target domain, so the source domain usually comes from external factors such as the search query or social network, which is sometimes impossible to obtain. To handle the two problems, we propose a model that can extract both homogeneous and divergent features among domains and extract data in a domain can support for other domain equally: a so-called Domain-to-Domain Translation Model (D2D-TM). It is based on generative adversarial networks (GANs), Variational Autoencoders (VAEs), and Cycle-Consistency (CC) for weight-sharing. We use the user interaction history of each domain as input and extract latent features through a VAE-GAN-CC network. Experiments underscore the effectiveness of the proposed system over state-of-the-art methods by a large margin.

Many conversational agents in the market today follow a standard bot development framework which requires training intent classifiers to recognize user input. The need to create a proper set of training examples is often the bottleneck in the development process. In many occasions agent developers have access to historical chat logs that can provide a good quantity as well as coverage of training examples. However, the cost of labeling them with tens to hundreds of intents often prohibits taking full advantage of these chat logs. In this paper, we present a framework called \textit{search, label, and propagate} (SLP) for bootstrapping intents from existing chat logs using weak supervision. The framework reduces hours to days of labeling effort down to minutes of work by using a search engine to find examples, then relies on a data programming approach to automatically expand the labels. We report on a user study that shows positive user feedback for this new approach to build conversational agents, and demonstrates the effectiveness of using data programming for auto-labeling. While the system is developed for training conversational agents, the framework has broader application in significantly reducing labeling effort for training text classifiers.

It wasn't so long ago that consumer robots were destined to be the next big thing. But, that optimism hasn't translated into consumer sales. The result: Jibo was sold for parts. It was one of the first social robots. The founder, MIT roboticist Cynthia Brezeal, was a favorite of tech media.

Google Assistant hasn't been traveling, but it has picked up some new accents. The voice assistant now has the ability to speak in an Australian or English accent (though Google calls it British). The feature is available across all devices including Android phones and Google Home speakers, but only for English speakers in the US for the time being. In order to produce the accents in an accurate way, Google is tapping into the artificial intelligence of DeepMind. Google Assistant uses WaveNet, the AI company's speech synthesis model powered by deep neural networks, to generate natural sounding voices.

Media streamers open up a whole world of content for cord-cutters, and right now you can grab the one we've called "the media streamer to beat" at a steep discount. Amazon's Fire TV 4K is on sale for $35, down from a list price of $50 and the lowest we've seen it. If you buy two, you can save even more, bringing the pair down to $60. It also comes with the rare useful streaming remote, with control over volume, TV power, and even a mute button all in one place. For hands-free control, the Fire TV 4K is compatible with Amazon's Alexa digital assistant, and can respond to your voice using either the microphone built into the remote or via connection to an Echo.

Surface Headphones are Microsoft's high-price, premium noise-cancelling cans aimed squarely at toppling the current kings, Bose and Sony. Headphones seem like an odd choice for the Xbox, Office and Windows maker, but the are being produced by Microsoft's burgeoning consumer electronics arm responsible for its line of Surface computers and accessories. Microsoft has aimed right for the top of the tree in terms of wireless, noise cancelling headphones. The fit and finish of the Surface Headphones is every bit as good as Bose. The large, soft round ear cups encapsulate my ears with their oval openings, while the angle of the band and hinge points give plenty of flexibility, avoiding any obvious pressure points.