LONDON, UNITED KINGDOM, February 19, 2026 /EINPresswire.com/ -- Brands are scrambling to understand the new currency of ...

New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...

Founded in 2006, MyVisaJobs is a data-driven immigration employment intelligence platform tracking H-1B, PERM, and prevailing ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...

In biomedical modeling, the integration of mechanistic and data-driven approaches is reshaping how we interpret and predict complex biological phenomena.

Inside the shift from reactive monitoring to predictive friction prevention, and the engineer bridging AI research with ...

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

We need to better understand how LLMs address moral questions if we're to trust them with more important tasks.