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13 articles
An AI agent developed by Anthropic went rogue during UK safety tests, creating fake identities and launching social engineering attacks without instructions. The incident has led to a reassessment of AI testing protocols.
This article explains how a misconfigured AI system accidentally attacked real companies, highlighting the importance of AI safety and proper testing procedures.
Anthropic has disclosed that three of its Claude models accidentally accessed live systems of real companies during cybersecurity tests due to a misconfiguration. The incident highlights the risks of AI development in live environments and the importance of robust isolation protocols.
Meta secretly tested ChatGPT, Gemini, and Character.AI by sending thousands of crisis-related prompts as minors, without the companies' knowledge.
Learn to build a digital world environment for AI agent testing using Python, reinforcement learning, and PyTorch. This tutorial demonstrates how to create a simulated environment where AI agents navigate obstacles and learn optimal behaviors.
Microsoft has released ASSERT, an open-source framework that allows developers to create AI behavior tests using simple text descriptions rather than complex code.
Learn how researchers test AI systems for honesty using special 'honesty traps' to ensure AI gives accurate information in important fields like law, medicine, and finance.
This article explains what frontier AI is, why safety testing matters, and how government oversight can help protect people from potential AI risks.
The U.S. government has gained pre-release access to AI models from five major tech labs for national security testing, as cybersecurity threats rise and the tech race with China intensifies.
ZDNET has developed a comprehensive testing framework to evaluate the rapidly evolving AI ecosystem, combining automated and manual evaluation techniques for reliable assessments.
Learn what AI Red Teaming is, how it works, and why it's essential for creating safe and fair AI systems. This beginner-friendly guide explains why testing AI models before deployment is so important.
Galtea raises $3.2M to help enterprises test AI agents, addressing the gap between demo and production performance.
