Google announced a giant slew of updates to its various software products at its I/O developer conference this week, and in addition to Android, Wear, Assistant and a ton of other news, it's not forgetting about the smart home. At the show, the company shared a few updates around its Nest and Android products that focus on a commitment to the recently renamed Matter ecosystem. As a recap, Matter was formerly known as Project CHIP, or Connected Home over IP. It's a collaboration between industry giants like Google, Amazon, Apple, Samsung and more to standardize the historically fragmented smart home ecosystem. Matter will support a variety of protocols and assistants, including Siri, Alexa, the Google Assistant as well as Bluetooth, Ethernet, WiFi and Thread.

It's a question that has baffled most men for years – what do women want? Now, a new survey has revealed exactly what females rate the highest when it comes to sexual attraction, as well as what men's priorities are. The findings suggest that while women rate age, income and personality highly, men are more focused on looks. The researchers suggest that these differences may occur as a result of the fact that women's window for reproduction is more limited than men's, so they'can't risk choosing poorly.' In the study, researchers from Queensland University of Technology in Brisbane surveyed 7,325 users of dating websites about what they look for in a potential partner.

It's no secret that voice recognition has advanced significantly since IBM introduced its first speech recognition machine in 1962. With voice-driven applications like Amazon's Alexa, Apple's Siri, Microsoft's Cortana, and many voice-responsive features of Google, voice recognition has become increasingly embedded in our daily lives as technology has evolved. Every new voice-interactive device we introduce into our lives, from phones to computers to watches to refrigerators, increases our reliance on artificial intelligence (AI) and machine learning. Artificial intelligence is one disruptive technology that has altered the way valuable data is handled. When working with large analyzable sets of data, such as text, machine learning is thought to be at its best.

"I have nothing to hide" was once the standard response to surveillance programs utilizing cameras, border checks, and casual questioning by law enforcement. Privacy used to be considered a concept generally respected in many countries with a few changes to rules and regulations here and there often made only in the name of the common good. Things have changed, and not for the better. China's Great Firewall, the UK's Snooper's Charter, the US' mass surveillance and bulk data collection -- compliments of the National Security Agency (NSA) and Edward Snowden's whistleblowing -- Russia's insidious election meddling, and countless censorship and communication blackout schemes across the Middle East are all contributing to a global surveillance state in which privacy is a luxury of the few and not a right of the many. As surveillance becomes a common factor of our daily lives, privacy is in danger of no longer being considered an intrinsic right. Everything from our web browsing to mobile devices and the Internet of Things (IoT) products installed in our homes have the potential to erode our privacy and personal security, and you cannot depend on vendors or ever-changing surveillance rules to keep them intact. Having "nothing to hide" doesn't cut it anymore. We must all do whatever we can to safeguard our personal privacy. Taking the steps outlined below can not only give you some sanctuary from spreading surveillance tactics but also help keep you safe from cyberattackers, scam artists, and a new, emerging issue: misinformation. Data is a vague concept and can encompass such a wide range of information that it is worth briefly breaking down different collections before examining how each area is relevant to your privacy and security. A roundup of the best software and apps for Windows and Mac computers, as well as iOS and Android devices, to keep yourself safe from malware and viruses. Known as PII, this can include your name, physical home address, email address, telephone numbers, date of birth, marital status, Social Security numbers (US)/National Insurance numbers (UK), and other information relating to your medical status, family members, employment, and education. All this data, whether lost in different data breaches or stolen piecemeal through phishing campaigns, can provide attackers with enough information to conduct identity theft, take out loans using your name, and potentially compromise online accounts that rely on security questions being answered correctly. In the wrong hands, this information can also prove to be a gold mine for advertisers lacking a moral backbone.

By this point in the pandemic, it's safe to say most of us would be happy if we didn't have to attend another Zoom call ever again. But with COVID-19 still an ongoing concern and companies like Google moving to hybrid work weeks, it's fair to say video meetings will likely be a consistent fixture of most jobs for the foreseeable future. Audio transcription company Otter thinks it has a potential solution for Zoom fatigue. It's introducing a new software feature called Otter Assistant that will attend Zoom calls on your behalf and take notes for you. The company says the tool works with all Zoom meetings, even ones where you're not the host.

Conversational agents (CAs) represent an emerging research field in health information systems, where there are great potentials in empowering patients with timely information and natural language interfaces. Nevertheless, there have been limited attempts in establishing prescriptive knowledge on designing CAs in the healthcare domain in general, and diabetes care specifically. In this paper, we conducted a Design Science Research project and proposed three design principles for designing health-related CAs that embark on artificial intelligence (AI) to address the limitations of existing solutions. Further, we instantiated the proposed design and developed AMANDA - an AI-based multilingual CA in diabetes care with state-of-the-art technologies for natural-sounding localised accent. We employed mean opinion scores and system usability scale to evaluate AMANDA's speech quality and usability, respectively. This paper provides practitioners with a blueprint for designing CAs in diabetes care with concrete design guidelines that can be extended into other healthcare domains.

Amazon's Echo Frames are compatible with most prescription lenses, but they only come with clear lenses out of the box -- until now, anyway. The retail giant has introduced three new options to choose from if you're looking to buy a pair of the Alexa-powered eyewear. You can get it with polarized blue mirror sunglass lenses starting today, and starting on June 9th, you can get a pair with blue-light-filtering lenses and polarized classic sunglass lenses. The Echo Frames have open-ear audio near your temples, so you can listen to music, audiobooks and podcasts, as well as take calls without blocking the world around you. Since it also gives you hands-free access to Alexa, you can simply issue voice commands to control it, such as "Alexa, play my followed podcasts on Amazon Music" or "Alexa, resume my audiobook."

If your home is kitted out with Amazon Echo devices, you can now use the "drop in" feature to talk to all of them at the same time. This essentially brings a quick and easy intercom to your home. Up until now, you could use Amazon's "drop in" feature to send a voice message to only one other Alexa-powered device. Let's say from the Amazon Echo in your living room to the Amazon Echo Dot in your kitchen. You could "drop in" then start a conversation that works both ways.

When it came to talking about the harmful effects of social media on kids, I used to feel like the Will Smith character in I, Robot: "Why won't anyone listen to me?" After I wrote a book about girls and social media in 2016, I got a lot of pushback from people accusing me of being a Luddite or raising a moral panic. That changed over time, once a deluge of studies sadly connected social media use in girls with rising rates of anxiety and depression, the loss of self-esteem, even suicide. Today, I don't think anyone would argue that social media is without significant dangers for children and teens. Nancy Jo Sales is the author of American Girls: Social Media and the Secret Life of Teenagers and Nothing Personal: My Secret Life in the Dating App Inferno.

Performance of recommender systems (RS) relies heavily on the Many large scale e-commerce platforms (such as Etsy, Overstock, amount of training data available. This poses a chicken-and-egg etc) and online content platforms (such as Spotify, Overstock, Disney, problem for early-stage products, whose amount of data, in turn, Netflix, etc) have such a large inventory of items that showcasing relies on the performance of their RS. On the other hand, zero-shot all of them in front of their users is simply not practical. In learning promises some degree of generalization from an old dataset particular, in the online content category of businesses, it is often to an entirely new dataset. In this paper, we explore the possibility seen that users of their service do not have a crisp intent in mind of zero-shot learning in RS. We develop an algorithm, dubbed ZEro-unlike in the retail shopping experience where the users often have Shot Recommenders (ZESRec), that is trained on an old dataset a crisp intent of purchasing something. The need for personalized and generalize to a new one where there are neither overlapping recommendations therefore arises from the fact that not only it is users nor overlapping items, a setting that contrasts typical crossdomain impractical to show all the items in the catalogue but often times RS that has either overlapping users or items. Different users of such services need help discovering the next best thing from categorical item indices, i.e., item ID, in previous methods, -- be it the new and exciting movie or be it a new music album or ZESRec uses items' natural-language descriptions (or description even a piece of merchandise that they may want to consider for embeddings) as their continuous indices, and therefore naturally future buying if not immediately.