By 2036, healthcare IT will likely be unlike anything we see today — not because of a single breakthrough technology, but because of how deeply digital tools are embedded into care delivery. Across ...

Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...

Algorithmic transparency is another critical issue. AI systems often operate as complex, opaque models, making it difficult for users to understand how decisions are made. This lack of transparency ...

When emotional data is read in context and combined with behavioral, operational and external signals, it becomes a predictor ...

Waiting for alerts is obsolete — predictive engineering lets cloud systems see trouble coming and fix it before users ever notice. For more than two decades, IT operations has been dominated by a ...

This variability can lead to differences in how physicians assess a patient's readiness for discharge. Less experienced physicians might be more cautious, which is one contributing factor to the ...

Can anyone remember their life before artificial intelligence (AI)? Many struggle with that, but what I do remember is how things worked in the business sector, especially in education.

AI market forecasting is reshaping how organizations anticipate demand, risk, and opportunity by processing massive volumes of structured and unstructured data in near real time. Modern systems ingest ...

Unscheduled machine downtime remains one of the biggest challenges in manufacturing. Festo's AX Motion Insights Electric and Pneumatic apps address this by combining the company’s hardware expertise ...

While not as mature as its use in other areas, health systems across the U.S. are beginning to adopt predictive analytics tools for labor cost forecasting. Many organizations have automated ...