Data analytics is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions. Artificial Intelligence (AI) is where we first heard the term cognitive technology. Technology experts began seeing the benefits of AI among consumer and business application. Amazon's Alexa and chatbots are two that come to mind that is now ubiquitous in homes and businesses.

SHOPPING: Products featured in this article are independently selected by our shopping writers. If you make a purchase using links on this page, MailOnline will earn an affiliate commission. Calling all bargain hunters, today shoppers can score a certified refurbished Amazon Echo Show 8 (1st Gen, 2019 release) and save 44 per cent off. Now discounted to just £59.99, marked down from £107.99, it's a great deal for those on a budget that want a smart home device with a display for video calls and home security. With an 8-inch HD screen, the Echo Show 8 is one of the retailer's most versatile Echo devices; it can display recipes, give you the weather, traffic updates and more.

With the huge growth in e-commerce domain, product recommendations have become an increasing field of interest amongst e-commerce companies. One of the more difficult tasks in product recommendations is size and fit predictions. There are a lot of size related returns and refunds in e-fashion domain which causes inconvenience to the customers as well as costs the company. Thus having a good size and fit recommendation system, which can predict the correct sizes for the customers will not only reduce size related returns and refunds but also improve customer experience. Early works in this field used traditional machine learning approaches to estimate customer and product sizes from purchase history. These methods suffered from cold start problem due to huge sparsity in the customer-product data. More recently, people have used deep learning to address this problem by embedding customer and product features. But none of them incorporates valuable customer feedback present on product pages along with the customer and product features. We propose a novel approach which can use information from customer reviews along with customer and product features for size and fit predictions. We demonstrate the effectiveness of our approach compared to using just product and customer features on 4 datasets. Our method shows an improvement of 1.37% - 4.31% in F1 (macro) score over the baseline across the 4 different datasets.

How can we accurately recommend actions for users to control their devices at home? Action recommendation for smart home has attracted increasing attention due to its potential impact on the markets of virtual assistants and Internet of Things (IoT). However, designing an effective action recommender system for smart home is challenging because it requires handling context correlations, considering both queried contexts and previous histories of users, and dealing with capricious intentions in history. In this work, we propose SmartSense, an accurate action recommendation method for smart home. For individual action, SmartSense summarizes its device control and its temporal contexts in a self-attentive manner, to reflect the importance of the correlation between them. SmartSense then summarizes sequences of users considering queried contexts in a query-attentive manner to extract the query-related patterns from the sequential actions. SmartSense also transfers the commonsense knowledge from routine data to better handle intentions in action sequences. As a result, SmartSense addresses all three main challenges of action recommendation for smart home, and achieves the state-of-the-art performance giving up to 9.8% higher mAP@1 than the best competitor.

Chatbots and smart speakers don't seem so smart today. But soon, they will perform a multitude of tasks. Billions of people use instant messaging apps daily to exchange bite-sized chunks of information on platforms including WhatsApp, iMessage, WeChat, Signal, Slack, Facebook Messenger, and Snapchat. In fact, as of this year, the amount of time we spend on messaging apps may surpass our use of social networks. These messaging platforms have become increasingly sophisticated, with capabilities far beyond simply enabling users to send and receive text messages, photos, and videos.

Bumble sales climbed in the latest quarter, driven by higher spending by users on its dating apps as prepandemic conditions have largely returned. But the online dating company trimmed its 2022 revenue range to $920 million to $930 million, down from its prior forecast of $934 million to $944 million, largely due to a higher impact from foreign currency movements. Its outlook for sales in the current quarter also fell short of Wall Street expectations.

Algorithmic Transparency in Action: How and Why Do Companies Disclose Information on Algorithms? Does the Accent of an Intelligent Conversational Agent Matter? What makes users reliant on the virtual assistant?

Amazon has reduced the price of the Echo Show 5 by $45. With the 53 percent discount, you can buy the smart display for $40, or just $5 more than it was during Prime Day. Amazon offers the device in a trio of colors – Charcoal, Deep Sea Blue and Glacier White. All three models are currently on sale. Like its bigger sibling, the Echo Show 5 includes a sunrise alarm feature, allowing the display to slowly brighten as a way to wake you gently during dark winter mornings.

Google has introduced a web version of its popular Read Along educational app for teaching children to read. The website includes Read Along the virtual assistant Diya, a voice-enabled AI guiding and correcting kids as they practice reading. The Read Along website operates much like the Android app. Children can pick from different stories and word games. Diya monitors the child, using Google's speech recognition technology to spot mistakes and places where they are having trouble.

Artificial intelligence (AI) is the ability of machines to mimic human capabilities in a way that we would consider'smart'. You most likely have come across – or are aware of – AI applications such as self-driving cars, facial recognition, chess or go players, security systems, or speech/voice recognition (for example, those used in an intelligent virtual assistant). In conventional computing, a programmer writes a computer program that precisely instructs a computer what to do to solve a particular problem. With AI, however, the programmer instead writes a program that allows the computer to learn to solve a problem by itself. That sounds like overdoing it, but this is really the way we do things.