Not just to your every word (waiting for you say "Alexa"), but also to the widespread criticism of the audio quality on the new Echo. The company issued a software update on Friday to improve the second-generation Echo's sound profile. It should have installed automatically, meaning you may have already noticed a bit more bass in your music this weekend. You can see if you have the latest software by looking under the Settings section of your Alexa app. The version number should be "592452420."

One of the most visible ways artificial intelligence (AI) is entering the business world is the consumer-facing chatbot. This AI-powered virtual assistant uses natural language processing to understand key words and context from customers and help them without the use of a human representative. Naturally, this offers powerful incentives to companies looking to offer 24/7 customer service without ballooning costs. But how are consumers reacting to chatbots? Are they really an effective way to augment customer service or are they a finicky, early stage technology that still has too many bugs to work out?

Wi-Fi-enabled smart lights are rapidly becoming commodities, and it's exciting to see prices plummeting to the point where they make sense for just about everyone. The latest: Eufy, a sub-brand of everything-goes electronics manufacturer Anker, just hit the market with two new affordable Edison-style smart bulbs: a $30 tunable-white bulb and a $20 fixed-white bulb. Eufy ticks off nearly all the specs one could ask for in a smart lighting system. Both the tunable and white-only bulbs operate at a solid 800 lumens while drawing 11 watts of power, work without a hub, and can be controlled with voice commands via Amazon's Alexa digital assistant. The bulbs even support external dimmers (though you may encounter trouble with the wireless radio working while they're dimmed).

Wi-Fi security cameras are becoming more of a fixture in smart homes thanks to integrations with Amazon Alexa, SmartThings, and even IFTTT. But D-Link's Omna 180 Cam HD ($150) is the first camera certified to work with Apple's HomeKit platform. That makes this camera a slam-dunk purchase for some users, but a more difficult sell for others. Given its alliance with Apple, it's not surprising the Omna is long on looks. Its silver body recalls the anodized aluminum finish of many Apple products, and its sleek, cylindrical form evokes that company's attention to design.

Smart home speakers have quickly become the hot gadget people didn't know they wanted. They can answer your movie trivia questions, call a cab, turn your heating on and do your shopping for you. They're gaining new features every day, but are more than just a utility product. These speakers are a ripe platform for all kinds of screen-free entertainment, and I'm not just talking about streaming a Spotify playlist. Earplay is a popular Alexa skill that tells interactive stories, for example, and never one to be late to a fledgling medium, the BBC has taken note.

Voice shopping might be the latest trend this holiday season, with major retailers having already partnered with leading voice assistants to offer shopping experience to users. While Target and Walmart have teamed up with the Google Express service, Best Buy is now selling a limited category of products through Amazon's Alexa voice assistant. With the biggest shopping festival of the year -- Black Friday -- being held on Nov. 24, chances are that Alexa's parent company, Amazon, may offer special offers for the holiday via the shopping assistant. If you are using Alexa, you will be able to learn about and make purchases on Best Buy's products, including its Deal of the day. If you are confused about which laptop or TV you should go for, the voice assistant will ask you a series of questions and recommend products based on your answers.

There are two main approaches taken in recommendation systems: content filtering and collaborative filtering. Content filtering makes use of features associated with items and users (e.g., age, location, gender of users and genre, director of movies). In contrast, collaborative filtering is based on observed user preferences. Thus, two users are thought of as similar if they have revealed similar preferences irrespective of their profile. Likewise, two items are thought of as similar if most users have similar preferences for them. More generally, collaborative filtering (CF) makes use of structure in the matrix of preferences, as in low-rank matrix formulations [1, 4, 8, 13, 14, 19, 20, 25]. An important aspect of most recommendation systems is that each recommendation influences what is learned about the users and items, which in turn determines the possible accuracy of future recommendations. This introduces a tension between exploring to obtain information and exploiting existing knowledge to make good recommendations. The tension between exploring and exploiting is exactly the phenomenon of interest in the substantial literature on the multi-armed bandit (MAB) problem and its variants [7, 16, 21].

We hope you didn't ask your shiny new Apple Watch about the weather on November 4th -- you probably got a rude response. Many Series 3 owners reported that their wristwear crashed (specifically, the "springboard" interface restarted) if they asked Siri how the weather was that day. It wouldn't crash if they asked about weather in subsequent days, but the odd hiccup affected users across North America and Europe. We've asked Apple for comment. With that said, there's already a potential culprit... and it's a familiar one for iPhone users.

Inc. Echo Spot, from left, Echo, Echo Plus, and Fire TV devices sit on display during the company's product reveal launch event in downtown Seattle, Washington, U.S., on Wednesday, Sept. 27, 2017. According to a new report, Singapore is on the cusp of the voice technology revolution. Nearly half of the population has tried voice technology services such as Apple's Siri, Samsung's S Voice and Google Assistant, and a quarter of them use such services monthly. With Amazon entering the market this year, the potential for further uptake is high as more advanced products and applications hit the market. Voice technology has been with us for many years now – from automated voice recognition phone systems that failed to understand accents, to simple voice-to-text dictaphones that produced inaccurate copy – but the failings of these systems prevented widespread uptake.

Recommender systems have been widely adopted by electronic commerce and entertainment industries for individualized prediction and recommendation, which benefit consumers and improve business intelligence. In this article, we propose an innovative method, namely the recommendation engine of multilayers (REM), for tensor recommender systems. The proposed method utilizes the structure of a tensor response to integrate information from multiple modes, and creates an additional layer of nested latent factors to accommodate between-subjects dependency. One major advantage is that the proposed method is able to address the "cold-start" issue in the absence of information from new customers, new products or new contexts. Specifically, it provides more effective recommendations through sub-group information. To achieve scalable computation, we develop a new algorithm for the proposed method, which incorporates a maximum block improvement strategy into the cyclic blockwise-coordinate-descent algorithm. In theory, we investigate both algorithmic properties for global and local convergence, along with the asymptotic consistency of estimated parameters. Finally, the proposed method is applied in simulations and IRI marketing data with 116 million observations of product sales. Numerical studies demonstrate that the proposed method outperforms existing competitors in the literature.