'We may see a dazzling array of products and services spawned by AI, but few of us will be able to buy them.' 'We may see a dazzling array of products and services spawned by AI, but few of us will be able to buy them.' The bogus four-day workweek that AI supposedly'frees up' Business leaders tout AI as a path to shorter weeks and better balance. The front-page headline in a recent Washington Post was breathless: "These companies say AI is key to their four-day workweeks. " The subhead was euphoric: "Some companies are giving workers back more time as artificial intelligence takes over more tasks." As the explained: "more companies may move toward a shortened workweek, several You may have come across similar articles in Fortune magazine and the New York Times. The AI spin brigade is in full force. Business leaders are rhapsodizing about how AI will free their employees to take more time off. Zoom's Eric Yuan told the Times that "A.I. can make all of our lives better, why do we need to work for five days a week?

This paper presents a deployed, production-grade system designed to enhance and scale search query datasets for intent-based recommendation systems in digital banking. In real-world environments, the growing volume and complexity of user intents create substantial challenges for data management, resulting in suboptimal recommendations and delayed product onboarding. To overcome these challenges, our approach shifts the focus from model-centric enhancements to automated, data-centric strategies. The proposed system integrates three core modules: Synthetic Query Generation, Intent Disambiguation, and Intent Gap Analysis. Synthetic Query Generation produces diverse and realistic user queries. Our experiments reveal no statistically significant difference when using synthetic data for Clinc150, while Banking77 and a proprietary dataset show significant differences. We dig into the underlying factors driving these variations, demonstrating that our approach effectively alleviates the cold start problem (i.e. the challenge of recommending new products with limited historical data). Intent Disambiguation refines broad and overlapping intent categories into precise subintents, achieving an F1 score of 0.863 $\pm$ 0.127 against expert reannotations and leading to clearer differentiation and more precise recommendation mapping. Meanwhile, Intent Gap Analysis identifies latent customer needs by extracting novel intents from unlabeled queries; recovery rates reach up to 71\% in controlled evaluations. Deployed in a live banking environment, our system demonstrates significant improvements in recommendation precision and operation agility, ultimately delivering enhanced user experiences and strategic business benefits. This work underscores the role of high-quality, scalable data in modern AI-driven applications and advocates a proactive approach to data enhancement as a key driver of value.

Rapid developments in AI and its adoption across various domains have necessitated a need to build robust guardrails and risk containment plans while ensuring equitable benefits for the betterment of society. The current technology-centered approach has resulted in a fragmented, reactive, and ineffective policy apparatus. This paper highlights the immediate and urgent need to pivot to a society-centered approach to develop comprehensive, coherent, forward-looking AI policy. To this end, we present a Social Outcomes and Priorities centered (SOP) framework for AI policy along with proposals on implementation of its various components. While the SOP framework is presented from a US-centric view, the takeaways are general and applicable globally.

Retrieval augmented generation (RAG) has been applied in many scenarios to augment large language models (LLMs) with external documents provided by retrievers. However, a semantic gap exists between LLMs and retrievers due to differences in their training objectives and architectures. This misalignment forces LLMs to passively accept the documents provided by the retrievers, leading to incomprehension in the generation process, where the LLMs are burdened with the task of distinguishing these documents using their inherent knowledge. This paper proposes R$^2$AG, a novel enhanced RAG framework to fill this gap by incorporating Retrieval information into Retrieval Augmented Generation. Specifically, R$^2$AG utilizes the nuanced features from the retrievers and employs a R$^2$-Former to capture retrieval information. Then, a retrieval-aware prompting strategy is designed to integrate retrieval information into LLMs' generation. Notably, R$^2$AG suits low-source scenarios where LLMs and retrievers are frozen. Extensive experiments across five datasets validate the effectiveness, robustness, and efficiency of R$^2$AG. Our analysis reveals that retrieval information serves as an anchor to aid LLMs in the generation process, thereby filling the semantic gap.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. In early November, Bentley University and Gallup released the results of its 2023 Bentley-Gallup Business and Society Report, which among other topics, focuses a portion of its study on surveying Americans on their opinions of how businesses will use artificial intelligence (AI) technologies in the future. When asked "In general, how much do you trust businesses to use artificial intelligence responsibly?", What is particularly telling, is that across education levels, ethnic background, age groups, and political party, the range of those trusting AI a "lot/some" was only between 17% and 28%.

Today PCWorld is launching Smart Answers, a chatbot tool that helps you get more from our content. It's built using Generative AI and existing content written by our human editors. The way we interact with content is changing. It wasn't so long ago you would have sifted through a printed magazine for advice on the latest consumer technology, yet it felt like a revolution when those old mags switched over to digital and online editions. These days, everything you could ever want to read is on the internet--or just as likely on YouTube or TikTok.

In recent years, Artificial intelligence products and services have been offered potential users as pilots. The acceptance intention towards artificial intelligence is greatly influenced by the experience with current AI products and services, expectations for AI, and past experiences with ICT technology. This study aims to explore the factors that impact AI acceptance intention and understand the process of its formation. The analysis results of this study reveal that AI experience and past ICT experience affect AI acceptance intention in two ways. Through the direct path, higher AI experience and ICT experience are associated with a greater intention to accept AI. Additionally, there is an indirect path where AI experience and ICT experience contribute to increased expectations for AI, and these expectations, in turn, elevate acceptance intention. Based on the findings, several recommendations are suggested for companies and public organizations planning to implement artificial intelligence in the future. It is crucial to manage the user experience of ICT services and pilot AI products and services to deliver positive experiences. It is essential to provide potential AI users with specific information about the features and benefits of AI products and services. This will enable them to develop realistic expectations regarding AI technology.

A robot which could work as a nurse or barman, and which can pick up objects with its human-like arms is already at work in the U.S., the CEO of a company funded by OpenAI, maker of ChatGPT has revealed. Bernt Bornich, CEO and founder of 1X, says that his company's humanoid EVE robot has been working since April this year - and that it is going'better than we thought.' It's the first truly humanoid android to find a place in the workplace in human history - outpacing Elon Musk's hyped Tesla robot. At present, the robot is working as a security guard at two industrial sites: unlike other security robots, it has a head, a face, two arms, and can navigate autonomously. Security guards control a fleet of patrolling EVE androids, which are made at two sites in Norway and Dallas, and if anything happens to one of the units, they can'step into' the android's body through virtual reality. 'You're there in a second as if you were there,' Bornich says.

In the past several decades, the world's economy has become increasingly globalized. On the other hand, there are also ideas advocating the practice of ``buy local'', by which people buy locally produced goods and services rather than those produced farther away. In this paper, we establish a mathematical theory of real price that determines the optimal global versus local spending of an agent which achieves the agent's optimal tradeoff between spending and obtained utility. Our theory of real price depends on the asymptotic analysis of a Markov chain transition probability matrix related to the network of producers and consumers. We show that the real price of a product or service can be determined from the involved Markov chain matrix, and can be dramatically different from the product's label price. In particular, we show that the label prices of products and services are often not ``real'' or directly ``useful'': given two products offering the same myopic utility, the one with lower label price may not necessarily offer better asymptotic utility. This theory shows that the globality or locality of the products and services does have different impacts on the spending-utility tradeoff of a customer. The established mathematical theory of real price can be used to determine whether to adopt or not to adopt certain artificial intelligence (AI) technologies from an economic perspective.

Evolution is a leading international B2B provider of games and services in online casino. Operating in the forefront of our industry, we offer a turn-key solution for casino operators. Our licensees' players can move flawlessly between mobile, tablet and desktop to play slots or live casino, which feature real tables with real dealers in real time. Our innovative and high-quality offer includes brands like Evolution Live, Red Tiger and NetEnt, and multiple award-winning international player product favorites, such as Crazy Time, Lightning Roulette and Gonzo's Quest. Evolution is listed on Nasdaq Nordic with a MCAP of EUR 20 BN.