Even though full enforcement won't begin until 2026–2027, the GPAI obligations are legally binding as of August. The smartest ...

‍ AI agents offer enterprises a transformational leap—not just in what gets done, but how it gets done. Their impact stems from the powerful intersection of: Speed AI agents operate 24/7 without ...

The harmful and benign prompts were sourced from a Cornell University dataset designed to rigorously test AI security, drawing from established red-teaming methodologies. While not a reasoning-based ...

Grok-3 audit reveals 2.7% jailbreaking resistance—far below rivals. Strengthen AI security with Holistic AI. Schedule a demo today!

Enhance AI governance with Holistic AI's advanced red teaming solutions. Test safeguards, improve safety, and ensure compliance seamlessly.

Explore privacy risks in machine learning, membership inference attacks, and the privacy risk score to enhance data security and build trustworthy AI systems.

In recent years, the growing focus on responsible AI has sparked the development of various libraries aimed at addressing bias measurement and mitigation. Among these, the holisticai open-source ...

Discover how to protect your enterprise from Shadow AI risks. Learn to detect unauthorized AI usage, ensure compliance, and securely harness AI's potential.

Discover Human-in-the-Loop AI: integrating human expertise with AI to ensure accuracy, ethical compliance, and adaptability in today’s technology landscape.

This blog post will provide an overview of what data contamination is, why it can be harmful, how to detect it, and how to mitigate it in the context of LLMS.

This blog post explores the essential role of LLM monitoring, including its significance, the challenges faced, and future trends in this vital aspect of AI oversight.

Large Language Models (LLMs) are advanced AI systems designed to understand and generate human-like text through extensive training on diverse and massive datasets, including books, articles, and ...