AWS Certified AI Practitioner

Correct Answer: B) Model Evaluation in Amazon Bedrock Console

Explanation:

Amazon Bedrock's Model Evaluation feature allows users to compare different foundation models on various metrics including speed (latency), accuracy, and other performance characteristics. This feature is specifically designed to help developers:

1. Compare multiple models - Test Anthropic Claude, Amazon Titan, AI21 Labs, Cohere, and other available models
2. Evaluate on specific tasks - Assess models for text summarization, question answering, classification, etc.
3. Measure performance metrics - Compare speed (latency), accuracy, cost, and other relevant metrics
4. Use built-in or custom datasets - Evaluate models using predefined datasets or your own custom data

Why other options are incorrect:

• A) Knowledge Bases: This feature is for creating vector databases and RAG (Retrieval Augmented Generation) applications, not for model comparison.
• C) Guardrails: This feature is for implementing content safety filters and responsible AI controls, not for performance comparison.
• D) Bedrock Pipelines: This is for creating orchestrated workflows and multi-step AI applications, not specifically for model evaluation and comparison.

The Model Evaluation feature in the Amazon Bedrock Console provides a systematic way to test and compare foundation models, which is exactly what the startup needs to determine which model performs best for their text summarization application in terms of both speed and accuracy.