Definition
Eval, or model evaluation, is the process of assessing the performance and quality of artificial intelligence models, particularly large language models. It involves using various metrics and techniques to determine how well a model performs its intended tasks, identifies biases, and adheres to safety guidelines. In practice, eval is integrated into the AI development lifecycle, from initial training through deployment and ongoing monitoring, to ensure models are reliable and effective. This systematic assessment is crucial for building trust in AI systems and mitigating potential risks associated with their use in critical applications. For instance, an organization might evaluate an LLM's ability to generate accurate medical summaries by comparing its output against human expert diagnoses. A common point of confusion is mistaking eval for simple testing. eval encompasses a broader, more rigorous assessment of model capabilities and ethical considerations. This concept is frequently tested on AI certification exams and within responsible AI frameworks.