Researchers are racing to develop more challenging, interpretable, and fair assessments of AI models that reflect real-world use cases. The stakes are high. Benchmarks are often reduced to leaderboard ...

AI agents are becoming a promising new research direction with potential applications in the real world. These agents use foundation models such as large language models (LLMs) and vision language ...

Many of the most popular benchmarks for AI models are outdated or poorly designed. Every time a new AI model is released, it’s typically touted as acing its performance against a series of benchmarks.

They could offer a more nuanced way to measure AI’s bias and its understanding of the world. New AI benchmarks could help developers reduce bias in AI models, potentially making them fairer and less ...