Remove Data Quality Remove Explainable AI Remove Prompt Engineering
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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

This includes handling unexpected inputs, adversarial manipulations, and varying data quality without significant degradation in performance. When you ask the model to explain the process it used to generate the output, the model has to identify different the steps taken and information used, thereby reducing hallucination itself.

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Understanding Generative AI Through Critical Thinking and Implementation

ODSC - Open Data Science

This approach, he noted, applies equally to leveraging AI in areas like data management, marketing, and customer service. Right now, effective prompt engineering requires a careful balance of clarity, specificity, and contextual understanding to get the most useful responses from an AI model.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

W&B (Weights & Biases) W&B is a machine learning platform for your data science teams to track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results, spot regressions, and share findings with colleagues. Data monitoring tools help monitor the quality of the data.