Ever since the original Echo Show, smart displays have proven to be pretty useful around the house. They're great for quickly looking up information, recipe instructions, video calls and more. As you're actively crisscrossing the kitchen while cooking a meal, you have to keep backtracking to look at the screen for the next step. Or if you're on a video call with mom and you walk away to make a cup of coffee, you're forced to become a disembodied voice as she converses with a wall. The all-new Echo Show 10, however, helps solve that problem.

NEW YORK (Reuters) - Thomson Reuters Corp will streamline technology, close offices and rely more on machines to prepare for a post-pandemic world, the news and information group said on Tuesday, as it reported higher sales and operating profit. The Toronto-headquartered company will spend $500 million to $600 million over two years to burnish its technology credentials, investing in AI and machine learning to get data faster to professional customers increasingly working from home during the coronavirus crisis. Thomson Reuters' New York- and Toronto-listed shares each gained more than 8%. It aims to cut annual operating expenses by $600 million through eliminating duplicate functions, modernizing and consolidating technology, as well as through attrition and shrinking its real estate footprint. Layoffs are not a focus of the cost cuts and there are no current plans to divest assets as part of this plan, the company said.

Artificial intelligence allows machines to understand and achieve specific goals. AI includes machine learning via deep learning.

Another huge change has been the extensive use of artificial intelligence, which is transforming digital strategies completely.

"Current machine text-generation models can write an article that may be convincing to many humans, but they're basically mimicking what they have seen in the training phase," said [PhD student Yuchen] Lin. "Our goal in this paper is to study the problem of whether current state-of-the-art text-generation models can write sentences to describe natural scenarios in our everyday lives." Essentially, fake news bots can sound like the New York Times or marketing copy by generating mimics, after taking in thousands of natural examples. Specifically, Ren and Lin tested the models' ability to reason and showed there is a large gap between current text generation models and human performance. Given a set of common nouns and verbs, state-of-the-art NLP computer models were tasked with creating believable sentences describing an everyday scenario.

Former Google CEO Eric Schmidt called on the US government to fast track development of emerging technology including artificial intelligence (AI) to …

Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want to convince users to purchase specific items. Users should better understand how the recommender system works and why a specific item has been recommended. Users should also develop a more in-depth understanding of the item domain. Consequently, explanations are designed in order to achieve specific \emph{goals} such as increasing the transparency of a recommendation or increasing a user's trust in the recommender system. In this paper, we provide an overview of existing research related to explanations in recommender systems, and specifically discuss aspects relevant to group recommendation scenarios. In this context, we present different ways of explaining and visualizing recommendations determined on the basis of preference aggregation strategies.

Intelligent machines and smart data can transform our world. This tech trio--artificial intelligence, machine learning, and data analytics--is the "glue" …

For their study, Misra and his team chose a type of machine-learning algorithm based on the concept of reinforcement learning. Simply put, the software …

Machine learning methods are providing computational scientists new tools to accurately and efficiently conduct these atomistic simulations.