Yet, traditional ITSM frameworks often rely heavily on manual processes that create inefficiencies, accuracy issues, and slow resolution times. As organizations scale and user demands grow more ...

Objectives This study was to estimate the potential social value and net benefit of OpenUp, a 24/7 text-based online counselling service for youth in Hong Kong, and draw policy-relevant conclusions ...

Generative AI (GenAI) is a type of AI that creates new content in response to user prompts and has become the most prevalent type of AI used in relation to tax scams and fraud. Scammers use GenAI ...

New architecture integrates Copilot, Azure OpenAI, Claude, and Perplexity to transform Microsoft Power BI into an AI-driven enterprise decision platform. At most organizations, Copilot is only the ...

Kennesaw State University (KSU) is stepping into the future of workforce-ready education with the launch of a new Bachelor’s degree in Artificial Intelligence beginning in Fall 2026. As AI rapidly ...

BrainWhisperer is Tether’s Brain-to-text project. Tether is earmarking resources to build technologies that push the borders of intracranial electrocortical decoding. The latest result is a variable ...

Smart city initiatives are generating vast amounts of data from sensors, cameras, mobile devices, and digital service ...

A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models creates significant challenges when AI systems attempt to represent fluid and ...

Last year, US banks used real-time machine learning to flag over 90 percent of suspected fraud, yet almost half of chargeback ...

Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldstein & Fox PLLC discuss challenges in meeting patent law's disclosure requirements for inventions involving artificial intelligence, ...

Abstract: To improve the performance of English-text classification, text classification systems aim to design appropriate algorithms for extracting features and auto-classifying texts with automatic ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...