Explore our latest resources and practical guides to navigate the evolving landscape of AI compliance and regulation.
Definición técnica Data governance is the organizational framework of policies, processes, standards, roles, and controls that determines how data is collected, stored, managed, used, shared, and retired across…
Definición técnica Model interpretability refers to the degree to which the internal mechanisms of an AI model can be understood by humans — specifically, the extent to which…
Definición técnica AI model lifecycle management is the structured governance framework that oversees an AI model from its initial conception through development, validation, deployment, operation, monitoring, retraining, and…
Definición técnica Model testing in AI systems is the systematic process of evaluating AI model performance, behavior, robustness, fairness, and safety against defined criteria before deployment and throughout…
Definición técnica Model validation is the structured process of evaluating whether an AI model meets its intended purpose, performs within acceptable parameters, and is suitable for deployment in…
Definición técnica Post-market monitoring (PMM) is the systematic, ongoing process of collecting, documenting, and analyzing data about the performance, reliability, and behavior of AI systems after they have…
Definición técnica What is grounding in generative AI systems? Grounding is the engineering practice of constraining a generative model's output to verifiable sources. Instead of relying on the…
Definición técnica MLOps (Machine Learning Operations) is the set of practices, tools, and cultural principles that streamline and automate the processes of deploying, monitoring, managing, and continuously improving…
Definición técnica A model card is a structured documentation artifact that provides concise, standardized information about a machine learning model: its intended use, performance characteristics, evaluation results across…
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