With the abundance of data in recent years, interesting challenges are posed in the area of recommender systems. Producing high quality recommendations with scalability and performance is the need of the hour. Singular Value Decomposition(SVD) based recommendation algorithms have been leveraged to produce better results. In this paper, we extend the SVD technique further for scalability and performance in the context of 1) multi-threading 2) multiple computational units (with the use of Graphical Processing Units) and 3) distributed computation. We propose block based matrix factorization (BMF) paired with SVD. This enabled us to take advantage of SVD over basic matrix factorization(MF) while taking advantage of parallelism and scalability through BMF. We used Compute Unified Device Architecture (CUDA) platform and related hardware for leveraging Graphical Processing Unit (GPU) along with block based SVD to demonstrate the advantages in terms of performance and memory.

You can save even more on the Ring Video Doorbell 2 when you order via Amazon Alexa. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. Our picks and opinions are independent from USA TODAY's newsroom and any business incentives. Round two of Amazon Prime Day 2019 is here and there are still plenty of amazing discounts to be had. Chances are you've probably spent time perusing a plethora of deals on Amazon, but have you tried using Alexa to save big?

The UK's National Health Service (NHS) has announced what it claims is a world first: a partnership with Amazon's Alexa to offer health advice from the NHS website. Britons who ask Alexa basic health questions like "Alexa, how do I treat a migraine?" The partnership does not add significantly to Alexa's skill-set, but it is an interesting step for the NHS. The UK's Department of Health (DoH) says it hopes the move will reduce the pressure on health professionals in the country, giving people a new way to access reliable medical advice. It will also benefit individuals with disabilities, like sight impairments, who may find it difficult to use computers or smartphones to find the same information.

Digital assistants have become a major trend in government at every level and across geographies, and could soon be a mainstay in many state and federal agencies in the U.S. Recent favorable signs include an executive order launching the American AI Initiative and the Health and Human Services Department awarding 57 spots on its Intelligent Automation/Artificial Intelligence (AI) contract, according to natural language processing (NLP) expert William Meisel, president of TMA Associates. Speaking at the AI World Government conference, held last month in Washington, D.C., Meisel says digital assistants (aka "intelligent" or "virtual" assistants) are among the most developed and least risky ways to implement AI--and "the closest to what we see in sci-fi." Digital assistants are broadly applicable across departments and agencies looking to cut costs and boost human productivity and have a minimum probability of failure and unintended consequences. For a citizenry looking for answers, they're also a "nice alternative to automated systems and long hold times," he adds. Juniper Research reports that, by 2023, one-quarter of the populace will be using digital voice assistants daily, says Meisel.

Want to keep an eye out for porch pirates? Or perhaps you're seeking a simpler way to see who is at your front door without having to get off the couch? Smart doorbells are still fairly new to the world of home security, and the market is becoming more and more saturated with options by the minute. This begs the question: How do you know which one is right for you and your home? I've been living with the Ring Video Doorbell Pro for about a year and a half now.

Perhaps you've heard the recent rumblings that Google is revamping its smart home line to exclusively include Nest products--and is rebranding under the name Google Nest. If not, here's a brief rundown of what happened: Google made the big announcement on May 7, indicating that Google Nest would be eliminating the Works with Nest program that allows Nest products to be controlled by smart assistants like Amazon Alexa. Since then, I've been wondering what exactly that means for how I'll control my Nest products going forward. I have a Nest thermostat and several Nest outdoor cameras and I often use Amazon Alexa (and the Nest app) to control these smart home devices. Other Nest users shared in my bewilderment, taking to Twitter to express their confusion about the merger.

Intelligent Personal Assistants (IPAs) have become widely popular in recent times. Most of the commercial IPAs today support a wide range of skills including Alarms, Reminders, Weather Updates, Music, News, Factual Questioning-Answering, etc. The list grows every day, making it difficult to remember the command structures needed to execute various tasks. An IPA must have the ability to communicate information about supported skills and direct users towards the right commands needed to execute them. Users interact with personal assistants in natural language. A query is defined to be a Help Query if it seeks information about a personal assistant's capabilities, or asks for instructions to execute a task. In this paper, we propose an interactive system which identifies help queries and retrieves appropriate responses. Our system comprises of a C-BiLSTM based classifier, which is a fusion of Convolutional Neural Networks (CNN) and Bidirectional LSTM (BiLSTM) architectures, to detect help queries and a semantic Approximate Nearest Neighbours (ANN) module to map the query to an appropriate predefined response. Evaluation of our system on real-world queries from a commercial IPA and a detailed comparison with popular traditional machine learning and deep learning based models reveal that our system outperforms other approaches and returns relevant responses for help queries.

In a world where technology is changing rapidly, it can be hard for businesses to keep up with shifting consumer demands. Take how customers interact with businesses, for instance. According to a recent study by Drift, people now prefer real-time interaction as they make their purchases, meaning that just having an online storefront is no longer enough. For startups looking to grow a loyal customer base, the immediate needs of users can be especially intimidating and even seem, at times, insurmountable. Entrepreneurs with small employee bases would have no way of being there for every customer and anticipating each person's needs in real time.

Amazon Alexa, which sits in your house and accepts voice commands enabling it to play music, activate lights, read news headlines and many other functions, is one of several intelligent personal assistants currently vying for dominance alongside Google Home and the Apple HomePod. Now however, Amazon is aiming to take this technology one step further by implementing it in to an actual robot that can not only answer questions, but also move autonomously around your home. Codenamed'Vesta', the new device is currently being worked on by Amazon's Lab126 research and development arm in Sunnyvale, California. According to reports, the web giant had intended to reveal the robot earlier this year but it wasn't quite ready for mass-production and more engineers have since been assigned to help speed things along. Rumor has it that the robot will be about waist-high and can navigate using an array of cameras.

With images aggregated from social media platforms, dating sites, or even CCTV footage of a trip to the local coffee shop, companies could be using your face to train a sophisticated facial recognition software. As reported by the New York Times, among the sometimes massive data sets that researchers use to teach artificially intelligent software to recognize faces is a database collected by Stanford researchers called Brainwash. More than 10,000 images of customers at a cafe in San Francisco were collected in 2014 without their knowledge. OKCupid and photo-sharing platforms like Flickr are among for researchers looking to load their databases up with images that help train facial recognition software. That same database was then made available to other academics, including some in China at the National University of Defense Technology.