Amazon SageMaker Clarify

Amazon SageMaker Clarify provides purpose-built tools to gain greater insights into your ML models and data, based on metrics such as accuracy, robustness, toxicity, and bias to improve model quality and support responsible AI initiative. With the rise of generative AI, data scientists and ML engineers can leverage publicly available foundation models (FMs) to accelerate speed-to-market. To remove the heavy lifting of evaluating and selecting the right FM for your use case, Amazon SageMaker Clarify supports FM evaluation to help you quickly evaluate, compare, and select the best FM for your use case based on a variety of criteria across different tasks within minutes. It allows you to adopt FMs faster and with confidence. For tabular, computer vision, and timeseries models, SageMaker Clarify provides model explainability during model development or post model deployment. You can use the bias and explainability reports to identify potential issues, and therefore direct efforts to improve accuracy, remove bias, and increase performance.