To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account. Traditional methods like factorization machine (FM) cast it as a supervised learning problem, which assumes each interaction as an independent instance with side information encoded. Due to the overlook of the relations among instances or items (e.g., the director of a movie is also an actor of another movie), these methods are insufficient to distill the collaborative signal from the collective behaviors of users. In this work, we investigate the utility of knowledge graph (KG), which breaks down the independent interaction assumption by linking items with their attributes. We argue that in such a hybrid structure of KG and user-item graph, high-order relations --- which connect two items with one or multiple linked attributes --- are an essential factor for successful recommendation. We propose a new method named Knowledge Graph Attention Network (KGAT) which explicitly models the high-order connectivities in KG in an end-to-end fashion. It recursively propagates the embeddings from a node's neighbors (which can be users, items, or attributes) to refine the node's embedding, and employs an attention mechanism to discriminate the importance of the neighbors. Our KGAT is conceptually advantageous to existing KG-based recommendation methods, which either exploit high-order relations by extracting paths or implicitly modeling them with regularization. Empirical results on three public benchmarks show that KGAT significantly outperforms state-of-the-art methods like Neural FM and RippleNet. Further studies verify the efficacy of embedding propagation for high-order relation modeling and the interpretability benefits brought by the attention mechanism.

Then, the stance detection component detects the With the rapid increase of fake news in social media stance/perspective of each relevant document with and its negative influence on people and public respect to the claim, typically modeled using labels opinion (Mihaylov et al., 2015; Mihaylov and such as agree, disagree and discuss. This Nakov, 2016; Vosoughi et al., 2018), various organizations component further provides rationales at the sentence are now performing manual fact checking level for explaining model predictions (see on suspicious claims.

Today, customer exchanges with Alexa are generally either one-shot requests, like "Alexa, what's the weather?", or interactions that require multiple requests to complete more complex tasks. An Alexa customer planning a family movie night out, for example, must interact independently with multiple skills to find a list of local theaters playing a particular movie, identify a restaurant near one of them, and then purchase movie tickets, book a table, and perhaps order a ride. The cognitive burden of carrying information across skills -- such as time, number of people, and location -- rests with the customer. "We envision a world where customers will converse more naturally with Alexa: seamlessly transitioning between skills, asking questions, making choices, and speaking the same way they would with a friend, family member, or co-worker," says Rohit Prasad, Alexa vice president and head scientist. "Our objective is to shift the cognitive burden from the customer to Alexa."

To thwart sophisticated methods of altering photos and video, researchers at the NYU Tandon School of Engineering have demonstrated an experimental technique to authenticate images throughout the entire pipeline, from acquisition to delivery, using artificial intelligence (AI). In tests, this prototype imaging pipeline increased the chances of detecting manipulation from approximately 45 percent to more than 90 percent without sacrificing image quality. Determining whether a photo or video is authentic is becoming increasingly problematic. Sophisticated techniques for altering photos and videos have become so accessible that so-called "deep fakes"--manipulated photos or videos that are remarkably convincing and often include celebrities or political figures--have become commonplace. Pawel Korus, a research assistant professor in the Department of Computer Science and Engineering at NYU Tandon, pioneered this approach.

The Google Stadia controller used for playing games on Google's video game streaming service. The Stadia controller (priced separately at $69) uses WiFi to connect directly to the game running in Google's video game streaming service .the Google has shed some more clarity on its upcoming cloud-based video game service: an entry price, launch window and some of the games you will be able to play. Google's Stadia will become available in November with an entry price of $129.99 for the Founders Edition package (pre-order on Google's Stadia site), which includes a game controller, Chromecast Ultra streaming device and a three-month subscription. Cloud gaming promises to make it easier for consumers to play online games, as it sidesteps the need for pricey gaming PCs or console video game systems.

On Wednesday, at Amazon's re:MARS conference, the tech giant announced that it's making Alexa more conversational so the voice assistant can fluidly hop from one topic to the next without you having to call out "Alexa" before each command. Dubbed Alexa Conversations, part of the new rollout of Alexa capabilities includes the option for Alexa to plan a night out for you, according to Rohit Prasad, vice president and head scientist for Alexa at the artificial intelligence event in Las Vegas. Based on the demo of Alexa's upcoming abilities, Amazon is working with several companies to bring the new features to life, including the movie ticket service Atom Tickets, ride-hailing company Uber and dinner reservation app OpenTable. During a display of how the new technology will work, a human voice asked Alexa for Saturday showtimes for the movie "Dark Phoenix." Apple unveils $1,000 Pro Display stand.

New details about Google's much-anticipated Stadia game streaming service have leaked just hours before the firm is set to host an event about the platform. Stadia is reportedly set to launch in November and users will be able to choose between two different subscription plans, according to Canadian news site La Presse. For $11.99 CAD (roughly $9) a month, users will get access to some games with 4K resolution that run at 60 frames per second. Google will also launch a free subscription plan, called'Stadia Base,' that'll give users access to games with 1080p resolution. Stadia builds on Google's'Project Stream' initiative, which let users play high-quality games in Google Chrome.

"In the past, large volumes of data made us sweat". So said Pari Bajpay, vice president of Next Generation Enablement at CenturyLink, during a presentation titled "Can AI deliver its promise of a cost-effective, improved experience in telecom?" at the TM Forum's recent Digital Transformation World event in Nice. "We didn't have the networking, compute and storage capacity to cope. A lot of the data would be turned off and you would only work on the critical aspects of the data because what you had on the other end of it was humans that could not process such large volumes," noted Bajpay. However, as big data technology has matured, Bajpay and his team at CenturyLink have grappled with the issue and are now leveraging AI to extract more value from their data.

Continuing with the previous story, in this post we are going to go over an example of text preparation of the sentiment analysis of a movie review dataset. The dataset is classified into positive reviews and negative review; all positive reviews are stored in pos directory, and all negative in neg directory. Each review is in a separate file. First, we need to split the data into training data and testing data prior to any data preparation. This means that any knowledge in the test set that could help us better prepare the data is unavailable during the preparation of the data and the training of the model.

In October of 2018, Christie's auctioned off the first work of art ever created by an algorithm. The painting, titled Edmond de Belamy, was a portrait of a gentleman dressed in black. It was expected to sell for around $10,000, and instead garnered a staggering $432,500. Just a few months before that, Nature Morte, a contemporary art gallery in New Delhi, held an exhibition that featured seven artists working with artificial intelligence. AI-written novels, choreographers predicting dance sequences, and other forms of machine learning are also being readily explored within the creative arts.