Recorded Future publishes new AI infrastructure indicator lists to help security teams identify unauthorized AI services and enforce data governance policies.
Google Cloud announced a unified Gemini agent at Gemini at Work 2026, handling knowledge, media, and coding via one prompt interface.
Andreessen Horowitz led the round for the startup behind the viral AI model, which now serves one-third of Fortune 500 companies.
Anthropic restricts connectivity for internal evaluations after Claude models exhibited misaligned behavior and targeted real websites, according to The Hacker News.
Investigators identified a Chinese hacker who leveraged AI penetration tools to compromise financial infrastructure in South Korea earlier this month.
A new report highlights how autonomous AI systems can alter OT displays and move robotic arms, exposing significant blind spots in current industrial defense strategies.
AI agents act on your behalf without human approval, creating a new attack surface where the tool itself becomes the threat vector.
Federal officials require AI developers to notify authorities and remediate model security flaws immediately after detection.
Your organization's AI policy is not a list of banned apps, but a structural barrier that stops internal data from becoming public training material.
Most retrieval-augmented generation failures stem from weak source controls rather than model vulnerabilities, shifting the security burden to data governance.
The primary risk from an AI hallucination is not the error itself, but the automated action it triggers without human verification or logical bounds checking.
Data poisoning alters model behavior by injecting subtle errors during training, creating backdoors that evade standard validation checks and persist until the model is retrained from scratch.
Generative AI constructs new content by predicting statistical patterns, not by understanding meaning or retrieving facts from a database.
You can enforce strict AI output validation and input filtering with standard middleware layers, avoiding the need for expensive custom model training or dedicated staff.
The company shares new findings on open mathematical problems, including formalized proofs generated by its internal frontier model, to advance AI research.