Computer scientist Azim Afroozeh redesigned data compression and storage so large datasets can be analyzed faster while taking less space.

From data poisoning to prompt injection, threats against enterprise AI applications and foundations are beginning to move from theory to reality.

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.

How Can Organizations Safeguard Machine Identities in the Cloud? Have you ever wondered how machine identities, also known as Non-Human Identities (NHIs), affect the security of your cloud-based ...

United States, 7th Jan 2026 - Noca AI today announced the availability of its enterprise AI agent platform designed to ...

Verified Market Research® a leading provider of business intelligence and market analysis is thrilled to announce the release of its comprehensive and authoritative report on the, "Healthcare ...

Americans are turning to artificial intelligence (AI) to help navigate the challenges of the U.S. healthcare system, according to the January 2026 report “AI as a Healthcare Ally: How Americans are ...

Errors are an unavoidable part of modern life. From minor human misjudgments to large-scale system failures, errors influence ...

The North Korean state-sponsored hacker group Kimsuki is using malicious QR codes in spearphishing campaigns that target U.S.

AI helps security teams move faster — but it’s also helping attackers do the same, turning cybersecurity into a race of ...

The lab, which expands upon an effort by UCSD and Scripps Research, will use wastewater analysis to detect flu, COVID and RSV ...

What are the differences between how AI systems handle JavaScript-rendered or interactively hidden content compared to ...