Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

Globally, toxic algal blooms are becoming more frequent and severe, fueled by a warming climate and nutrient runoff. While ...

Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...

The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.

The e-commerce giant quietly launched a feature that scrapes competitor websites without permission, and now hundreds of ...

Developed using Anthropic’s Claude AI model, the new language is intended to provide memory safety without garbage collection ...

Californians can now visit one state website to request all data brokers delete their personal information and refrain from ...

UF team earns international recognition for a study exposing privacy risks in AI image‑manipulation platforms and helping ...

A simple rule of thumb: In general, AI is best reserved for well-defined, repetitive tasks. This includes anything that ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...