Large language models are not just experimental tools limited to research labs. They now run smart chatbots and virtual ...

The findings show reasoning models aren't always more capable than non-reasoning ones, and the biggest safety gaps each company is grappling with.

OpenAI explains persistent “hallucinations” in AI, where models produce plausible but false answers. The issue stems from ...

RiskRubric provides a six-pillar framework to quantify AI model risk, guiding secure, compliant adoption with evidence-based ...

Amid the rapid proliferation of AI models, Podonos addresses growing demand for performance evaluation and validation, especially in the voice AI domain ...

Alibaba Group Holding’s 1 trillion-parameter Qwen3-max-preview model debuted in sixth place in the latest “text arena” ...

OpenAI finds a key problem in how large language models work. These models often give wrong information confidently. The ...

OpenAI has outlined the persistent issue of “hallucinations” in language models, acknowledging that even its most advanced systems occasionally produce confidently incorrect information.(Image by ...

Wang, S. (2025) A Review of Agent Data Evaluation: Status, Challenges, and Future Prospects as of 2025. Journal of Software ...

New joint safety testing from UK-based nonprofit Apollo Research and OpenAI set out to reduce secretive behaviors like scheming in AI models. What researchers found could complicate promising ...

For a long time, training large models has relied heavily on the guidance of a "teacher." This could either be human-annotated "standard answers," which are time-consuming and labor-intensive, or ...