Remove Auto-classification Remove Prompt Engineering Remove Responsible AI
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From concept to reality: Navigating the Journey of RAG from proof of concept to production

AWS Machine Learning Blog

The brand might be willing to absorb the higher costs of using a more powerful and expensive FMs to achieve the highest-quality classifications, because misclassifications could lead to customer dissatisfaction and damage the brands reputation. You can use Amazon Bedrock Guardrails for implementing responsible AI policies.

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Evaluate the reliability of Retrieval Augmented Generation applications using Amazon Bedrock

AWS Machine Learning Blog

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. In this case, the model choice needs to be revisited or further prompt engineering needs to be done.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on.