From low-rise jeans to reruns of the sitcom Friends, generation Z has a seemingly endless appetite for 90s and early 00s nostalgia. Now that extends to their romantic lives, as Tinder has introduced a blind date feature to boost its popularity among young people – by enabling them to meet partners in a way that resembles the pre-smartphone era. The new feature on the dating app matches people based on preferences, and enables them to make conversation before they are allowed to view each other's photos. It will shortly be available in the US before being expanded globally. Tinder says the feature is intended to respond to demands from generation Z, usually defined as people born between 1997 and 2012, for more authentic connections as a backlash to online dating's earlier emphasis on superficial judgments based on preened Instagram-ready photos on dating profiles.

Tinder has launched a new feature that could bring back memories of dating in the pre-smartphone era. It's a new Fast Chat experience called Blind Date that pairs members before allowing them to view each other's profiles. Tinder says its purpose is to give users a "low-pressure way to put their personality first," since they'll have to rely on conversation to make a first impression. The mode, which was perhaps partly inspired by the popularity of Netflix dating show Love is Blind, pairs people up based on their answers to random icebreaker questions, such as "I put ketchup on ____." Participants then enter a timed chat with their only knowledge of each other being their answers to those questions.

Tens of thousands of smart people start their day with their personalized digest by Refind.

Financial services technology firm Refinitiv has launched a new artificial intelligence (AI) assistant for Microsoft Teams to provide financial professionals with stock market news and actionable insights. Refinitiv AI Alerts - which is powered by technology from AI specialist ModuleQ - uses permissions and Microsoft 365 interactions to automatically learn the user's individual priorities and recommends content based on email conversations and upcoming meetings. "Microsoft Teams has become an indispensable platform for professionals across financial services, with institutions accelerating their adoption, and increasingly integrating critical data and tools into the platform to simplify the workflow and user experience of professionals," said Andrea Remyn Stone, group head of data and analytics at London Stock Exchange Group, which owns Refinitiv. "Refinitiv AI Alerts brings critical content and insights to Refinitiv's customer base within this platform, allowing users to discover and act on timely information across Teams, Refinitiv solutions and Microsoft 365 seamlessly." The new solution is the latest result of Refinitiv's partnership with Microsoft, which has previously helped financial services organisations connect, collaborate and leverage data to make more informed decisions.

Cross-Domain Recommendation (CDR) has been popularly studied to utilize different domain knowledge to solve the data sparsity and cold-start problem in recommender systems. In this paper, we focus on the Review-based Non-overlapped Recommendation (RNCDR) problem. The problem is commonly-existed and challenging due to two main aspects, i.e, there are only positive user-item ratings on the target domain and there is no overlapped user across different domains. Most previous CDR approaches cannot solve the RNCDR problem well, since (1) they cannot effectively combine review with other information (e.g., ID or ratings) to obtain expressive user or item embedding, (2) they cannot reduce the domain discrepancy on users and items. To fill this gap, we propose Collaborative Filtering with Attribution Alignment model (CFAA), a cross-domain recommendation framework for the RNCDR problem. CFAA includes two main modules, i.e., rating prediction module and embedding attribution alignment module. The former aims to jointly mine review, one-hot ID, and multi-hot historical ratings to generate expressive user and item embeddings. The later includes vertical attribution alignment and horizontal attribution alignment, tending to reduce the discrepancy based on multiple perspectives. Our empirical study on Douban and Amazon datasets demonstrates that CFAA significantly outperforms the state-of-the-art models under the RNCDR setting.

The glitches we often see in conversational interfaces like Alexa and Siri reveal to us the unique human ability we have to deploy empathy in conversations and social life. But in order for artificially intelligent machines to learn, more and more we must express ourselves in a reduced language and must simplify the complex range of human expression into something AI can understand. As we learn to live within the narrow confines of the computer,we may increasingly begin to lose the creative expressive potential of our bodies and language,writes David Berry. The imitation game, better known as the Turing test, was developed by Alan Turing in 1950. As one of the early pioneers of computers, he argued that if a computer could imitate a human successfully, it might thereby be thought of as intelligent.

Grindr is tightening privacy controls for the Olympic Village in Beijing. Bloomberg has learned the gay dating app is blocking people outside the Village from using the location-based Explore feature to find athletes in or near the area. The move is meant to protect athletes from harassment or persecution so they can "feel confident" connecting with each other during the Winter Olympic Games, Grindr for Equality director Jack Harrison-Quintana said. Anyone who uses Grindr inside the Village will see a pop-up telling them people outside the area can't browse the locale using Explore. "Your privacy is important to us," Grindr says in the alert.

One of the stars of the working-out-from-home boom is struggling. Peloton won't go quietly though and is making some big changes. The company will replace the CEO and co-founder, John Foley, who will become executive chairman, with former Spotify COO Barry McCarthy reportedly set to step into his shoes. While Foley is sticking around, the company is cutting around 2,800 corporate positions -- these won't include Peloton's instructors who lead its live classes. The company said in a press release about the lay-offs that its "monthly membership will be complimentary for impacted team members for an additional 12 months."

In a busy hospital, a radiologist uses an artificial intelligence system to help her diagnose medical conditions based on patients' X-ray images. Using the AI system can help her make faster diagnoses, but how does she know when to trust the AI's predictions? Instead, she may rely on her expertise, a confidence level provided by the system itself, or an explanation of how the algorithm made its prediction -- which may look convincing but still be wrong -- to make an estimation. To help people better understand when to trust an AI "teammate," Massachusetts Institute of Technology researchers created a technique that guides humans to a more accurate understanding of when a machine makes correct predictions and when it makes incorrect ones. The research is supported by the U.S. National Science Foundation.

Consumers have incredibly high expectations for companies to deliver faster and more personalized experiences, which is fueling the demand for Artificial Intelligence (AI) solutions. In turn, the increase in this utilization of AI is driving growth for many startups. Here are some AI tactics you can use today to scale and grow your business. Around 90 percent of consumers consider an immediate response important, and they demand a connected experience whenever they interact with a brand. Therefore, more organizations are investing in smarter solutions for better customer support. One of the simplest ways to do this is to embrace AI-powered applications, such as chatbots, voice search, and virtual assistants to improve customer experience.