If you've ever wanted to crumple up a keyboard and carry it in your pocket, researchers from the Sejong University in Korea have created a gadget that can do just that. Bendable portable keyboards have already been on the market for quite some time, but they are not very flexible and take up a significant amount of space. New technology uses silicone rubber embedded with conductive carbon nanotubes. The researchers have created a keyboard that is so thin, tough and flexible it can be crumpled up and put in a pocket with no damage. Existing keyboards use either rigid push buttons on a rollable sheet or a tactile sensor on a multilayered soft sheet.
In this interview, Priya Natarajan, senior director and head of worldwide go to market at Lenovo discusses the evolution of the data center and how artificial intelligence (AI) and machine learning (ML) are being used to streamline workloads and improve reliability. SDxCentral: Artificial intelligence (AI) and machine learning (ML) make it possible to automate some data center operations, but all this data that is collected can overwhelm networks. How does Lenovo see AI and ML impacting the data center? Priya Natarajan: Data center technologies are evolving rapidly to keep up with the growing volume of data. By observing patterns within the network, ML can be applied to understand the status of the network, identify bottlenecks and predict how it will react to future workloads.
Machine-learning technology powers many aspects of modern society: from web searches to content filtering on social networks to recommendations on e-commerce websites, and it is increasingly present in consumer products such as cameras and smartphones. Machine-learning systems are used to identify objects in images, transcribe speech into text, match news items, posts or products with users' interests, and select relevant results of search. Increasingly, these applications make use of a class of techniques called deep learning. Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data. In a simple case, you could have two sets of neurons: ones that receive an input signal and ones that send an output signal.
Urban Airship has raised $25 million in Series F funding. The company started out as a platform supporting push notifications, but has since expanded to include other marketing channels like email, SMS, mobile wallets and voice assistants. The goal is to be the platform managing messaging and unifying customer data across all these channels. Altogether, Urban Airship said it's now delivered more than two trillion messages, doubling the number from a year ago. Recent product additions include voice notifications on Amazon Alexa (which is still in beta testing) and automated in-app messaging.
In the world of SEO, it's important to understand the system you're optimizing for. Another crucial areas to understand is machine learning. Now, the term "machine learning" gets thrown around a lot these days. But how does machine learning actually impact search and SEO? This article will explore everything you need to know about how search engines use machine learning.
One of the most important things we learn as children is how to communicate with each other. We start with "goo goos and gaa gaas," then on to baby sign language, a few simple words like "momma," and our conversations get more complex from there. For the Google Assistant to have a natural conversation, it should be able to understand when it's being spoken to and should be capable of responding to several requests during an interaction. We're taking another step forward in making your interactions with the Google Assistant more natural with Continued Conversation, available starting today on Google Home, Google Home Mini and Google Home Max. We've heard from a lot of people that adding "Hey Google" before each follow-up question for the Assistant doesn't feel as natural as they'd like.
When you consider the popularity of Amazon's virtual assistant Alexa and the company's Fire TV streamers, it was really just a matter of time before the folks at the Everything Store decided to mash them up. In fact, Amazon already has, sort of: The company started down that path last year by giving Echo devices the ability to pass commands along to a Fire TV or Fire TV Stick. With the new Fire TV Cube, though, Amazon is trying to break down the wall between Alexa and the content you want to see altogether. Now, we've only had our Fire TV Cube for about two days, and that's just not enough time to really put the streaming box through its paces -- instead, read on for our first impressions about Amazon's new hardware and the virtual assistant that will ultimately make or break it. The Fire TV Cube itself is a glossy black box that, aside from the blue ring that lights up when Alexa is listening to you, looks about as nondescript as a bit of home theater kit can be.
If you're thinking of buying the Amazon Fire TV Cube because you're delighted by the idea of having an Amazon Echo and a Fire TV device mashed into one device, let me stop you right there. Alexa on a TV interface demands a level of conversation like no other streaming TV product I've used before. After a few nights of using the Cube, I began to hate the sound of my own voice. Maybe you'll still be delighted by the Cube at first if you buy one. Maybe if you have kids, they'll love shouting at the TV to get their cartoon fix.
Whether Father's Day, Mother's Day, a birthday or simply "just because," buying gifts can feel like counting grains of sand - i.e., it's not easy. Meanwhile, there are 250,ooo--300,000 e-commerce companies in the U.S. all vying for the attention of shoppers. How are consumers possibly expected to decide where to spend their hard-earned money? And how can retailers create a more personalized shopping experience, rather than facing the same demise as the 6,700 retail locations that closed their doors in 2017? In short, the retail sector is in a sticky wicket.
Amazon has announced a new program designed to help hotels deploy Alexa's voice-enabled smarts across their properties. Though Amazon's Alexa-powered Echo speakers are growing in popularity across the domestic realm -- helping users control their doors, lights, and search the web using nothing but their voice -- the internet giant has been targeting the hospitality sector for a while already. High-end hotel firm Wynn Resorts has been placing thousands of Amazon Echo speakers in its hotels since last summer, for example. And as of April, Alexa has been able to make phone calls in hotel rooms. Put simply, Amazon recognizes that hotels are a perfect showcase for its automated AI technologies.