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What is AI Quality? // Mohamed Elgendy // #228

MLOps.community

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Evolving AI Quality Standards and Testing

The chapter explores the journey from experimentation to engineering in machine learning, emphasizing the importance of effective data labeling and quality evaluation frameworks. It discusses the challenges and significance of testing in AI development, focusing on the differences from traditional software testing and the need for accuracy and factualness in responses. The conversation also touches on model cards as a means to establish trust and standardization in understanding model performance.

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