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This includes handling unexpected inputs, adversarial manipulations, and varying dataquality 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.
This approach, he noted, applies equally to leveraging AI in areas like data management, marketing, and customer service. Right now, effective promptengineering requires a careful balance of clarity, specificity, and contextual understanding to get the most useful responses from an AI model.
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.
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