If you waited until now to buy a smart speaker from Google, Amazon or Apple as a Christmas present, the pickings are going to be slim. Apple's $99 HomePod Mini, introduced in November as Apple's first consumer priced smart speaker, is sold out and not available until Jan. 4, according to Apple's website. Google's Nest Audio, the redesigned version of what had been called the Google Home, is also sold out, and not available until Jan. 8 at the earliest, with free delivery from Google's website, or Jan. 6 if consumers pay an extra $22.99 to expedite the order. Amazon's Echo Dot, the smallest and least expensive of its smart speaker lineup, has long been one of Amazon's holiday best sellers, ranking as its most purchased item last Christmas. This year there's a redesigned Dot with a built-in clock, but it's already sold out for the holidays.

The Nest Thermostat uses two AAA alkaline batteries to help power it, and they are included in your purchase. Here are the Nest Thermostat's basic specs: The new Nest Thermostat is a stripped-down and more affordable version of our favorite smart thermostat, Nest's Learning Thermostat. The latest model comes with mounting hardware but does not include a trim kit as the Nest Learning Thermostat does (though it can be purchased separately). It's also not smart enough to learn temperature preferences and habits over time, and instead of a built-in rechargeable battery like the Learning Thermostat has, the Nest Thermostat uses two AAA alkaline batteries. The Nest Thermostat does include many comparable features to the Nest Learning Thermostat like Eco Mode, Home/Away Assist, and scheduling features to help you save on energy costs, adding up to good value for the money.

Google is adding new games to Assistant-enabled smart displays like the Nest Hub to give people something new to play in time for the holidays. The additions fit broadly into three categories. In the first one, you'll find word games like Voice Quest. Here you'll play as a mage that casts spells using synonyms. In another new experience called Game of Words you'll have six letters with which you need to make as many words as possible.

Rejoice! Apple Music is finally available on Google Assistant-enabled smart speakers and displays like the Nest Audio and Nest Hub Max. Previously, only YouTube Music, Spotify, Pandora, and Deezer were able to be played natively on Google speakers. The addition of Apple Music to Google speakers is a welcome change for veteran iOS users who have previously relied on Bluetooth as a workaround to play from Apple's catalog of 70 million songs on Google Home speakers. Without further ado, here's how to start rocking out to Apple Music directly from Google speakers. Here's a look at how to link your Apple Music account in the Google Home app.

Google has announced that it's no longer making its music-focused Home Max smart speaker, which is--or was--the best-sounding smart speaker on the market. In a statement provided to TechHive, Google says that the $299 Home Max will continue to work normally, and that it will still offer software and security patches for the device. The statement also points smart speaker shoppers toward the Nest Audio, a new music-focused speaker with a smaller design and a more palatable $99 price tag. We've sold out of Google Home Max and will no longer be manufacturing the device. With the launch of Nest Audio, we're offering a range of great home audio solutions, particularly with two Nest Audios paired for stereo sound.

Although there are many good reasons to remember year 2020, but we have to accept the sad reality i.e. COVID-19 as well which is the major downside of same year. The best parts are the automation and the enhancement of customer experience through Companies are getting advanced in many ways to provide tailored and elegant solutions. Technologies like 5G (6G and Quantum computing are little far for now), cutting-edge medical diagnostics systems, real-time -powered e-commerce, consumer electronics, and smart personal assistants are few examples. 's bundle of joy (Machine learning and its advancement to and neural network) as horizontal scaling techniques have taken almost every other businesses and technology to the next level.

Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues (resp. singular values) and eigenvectors (resp. singular vectors) of some properly designed matrices constructed from data. A diverse array of applications have been found in machine learning, data science, and signal processing. Due to their simplicity and effectiveness, spectral methods are not only used as a stand-alone estimator, but also frequently employed to initialize other more sophisticated algorithms to improve performance. While the studies of spectral methods can be traced back to classical matrix perturbation theory and methods of moments, the past decade has witnessed tremendous theoretical advances in demystifying their efficacy through the lens of statistical modeling, with the aid of non-asymptotic random matrix theory. This monograph aims to present a systematic, comprehensive, yet accessible introduction to spectral methods from a modern statistical perspective, highlighting their algorithmic implications in diverse large-scale applications. In particular, our exposition gravitates around several central questions that span various applications: how to characterize the sample efficiency of spectral methods in reaching a target level of statistical accuracy, and how to assess their stability in the face of random noise, missing data, and adversarial corruptions? In addition to conventional $\ell_2$ perturbation analysis, we present a systematic $\ell_{\infty}$ and $\ell_{2,\infty}$ perturbation theory for eigenspace and singular subspaces, which has only recently become available owing to a powerful "leave-one-out" analysis framework.

In recent years, the field of recommendation systems has attracted increasing attention to developing predictive models that provide explanations of why an item is recommended to a user. The explanations can be either obtained by post-hoc diagnostics after fitting a relatively complex model or embedded into an intrinsically interpretable model. In this paper, we propose the explainable recommendation systems based on a generalized additive model with manifest and latent interactions (GAMMLI). This model architecture is intrinsically interpretable, as it additively consists of the user and item main effects, the manifest user-item interactions based on observed features, and the latent interaction effects from residuals. Unlike conventional collaborative filtering methods, the group effect of users and items are considered in GAMMLI. It is beneficial for enhancing the model interpretability, and can also facilitate the cold-start recommendation problem. A new Python package GAMMLI is developed for efficient model training and visualized interpretation of the results. By numerical experiments based on simulation data and real-world cases, the proposed method is shown to have advantages in both predictive performance and explainable recommendation.

Starting today, Alexa can translate conversations between two people who speak different languages. At launch, the digital assistant's new Live Translation feature works on Echo devices in the US and supports translation between English and French, German, Hindi, Italian, Spanish or Brazilian Portuguese. To start using the feature, ask Alexa to serve as an interpreter for the language that the person you want to talk to speaks. As the two of you converse, Alexa will automatically identify the person who's taking and translate as needed. If you own an Echo Show, you'll see a visual translation in addition to hearing an audio one.

You've heard so much about the new iPhones, and you want to get one. But seven models to choose from? And how to make your decision? "Upgrading from the XS Max soon," Wisconsin photographer Kevin Scott noted on Facebook. "Do you feel 12 Pro is worth the extra over the 12?" That was just one of the many questions we received during the holidays, which boiled down to variations of "Which iPhone should I buy?" and "Is the discounted Apple Watch a good buy?" You've come to the right place.