A company is using AI to improve its services. The company needs to ensure that the AI system is fair and explainable. The company wants to require training for members of the AI system development team.Which training will meet these requirements?
Answer(s): C
Training on bias awareness and responsible AI equips the development team with the knowledge and practices necessary to ensure that AI systems are fair, unbiased, and explainable, which aligns with the company’s requirements.
A company wants to integrate an AI solution to contact emergency services within 30 seconds of vehicle crash detection. The company wants to use a pre-trained model without additional training.Which factor should the company prioritize when selecting a model to meet these requirements?
Answer(s): B
Model size directly affects inference speed and latency, which is critical for meeting strict real-time response requirements such as contacting emergency services within 30 seconds using a pre-trained model.
A company deploys a foundation model (FM). The company notices that the FM is producing answers to user-submitted questions about politics. The company wants to ensure that the model does not send answers to political questions to users.Which AWS solution will meet this requirement?
Answer(s): A
Amazon Bedrock Guardrails allows you to define and enforce content policies, such as blocking or filtering responses to sensitive topics like politics, ensuring the model does not return prohibited outputs.
A company that runs AI workloads on Amazon Bedrock needs to evaluate and document compliance with regulatory standards.Which AWS service or feature meets these requirements?
AWS Audit Manager helps evaluate and document compliance with regulatory standards by continuously collecting evidence from AWS resources and mapping it to compliance frameworks. This supports audit preparation and governance for AI workloads running on AWS.
Which strategy will evaluate the performance of a foundation model (FM) in real-world applications?
A/B testing with users in a controlled environment evaluates how the foundation model performs in an actual application setting by measuring user interactions and outcomes under realistic conditions.
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