AIF-C01 Exam Dumps : AWS Certified AI Practitioner Exam

Amazon Bedrock Studio provides tools to build and manage generative AI applications, and the company needs a component to secure the content generated by AI systems. Guardrails in Amazon Bedrock are designed to ensure safe and responsible AI outputs by filtering harmful or inappropriate content, making them the key component for securing generated content.

Exact Extract from AWS AI Documents:

From the AWS Bedrock User Guide:

"Guardrails in Amazon Bedrock provide mechanisms to secure the content generated by AI systems by filtering out harmful or inappropriate outputs, such as hate speech, violence, or misinformation, ensuring responsible AI usage."

(Source: AWS Bedrock User Guide, Guardrails for Responsible AI)

Detailed Explanation:

Option A: Access controlsAccess controls manage who can use or interact with the AI system but do not directly secure the content generated by the system.

Option B: Function callingFunction calling enables AI models to interact with external tools or APIs, but it is not related to securing generated content.

Option C: GuardrailsThis is the correct answer. Guardrails in Amazon Bedrock secure generated content by filtering out harmful or inappropriate material, ensuring safe outputs.

Option D: Knowledge basesKnowledge bases provide data for AI models to generate responses but do not inherently secure the content that is generated.

A summarization chatbot is ideal for extracting key points from legal documents. Large language models (LLMs) can be used to summarize complex texts, such as legal documents, making them more accessible and understandable.

Option C (Correct): "Develop a summarization chatbot": This is the correct answer because a summarization chatbot uses LLMs to condense and extract key information from text, which is precisely the requirement for reading and summarizing legal documents.

Option A: "Build an automatic named entity recognition system" is incorrect because it focuses on identifying specific entities, not summarizing documents.

Option B: "Create a recommendation engine" is incorrect as it is used to suggest products or content, not summarize text.

Option D: "Develop a multi-language translation system" is incorrect because translation is unrelated to summarizing text.

AWS AI Practitioner References:

Using LLMs for Text Summarization on AWS: AWS supports developing summarization tools using its AI services, including Amazon Bedrock.

Amazon Bedrock is a fully managed service that provides access to foundation models (FMs) from various providers, enabling users to build and scale generative AI applications. It simplifies the process of integrating FMs into applications for tasks like text generation, chatbots, and more.

Exact Extract from AWS AI Documents:

From the AWS Bedrock User Guide:

"Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI providers available through a single API, enabling developers to build and scale generative AI applications with ease."

(Source: AWS Bedrock User Guide, Introduction to Amazon Bedrock)

Detailed Explanation:

Option A: Amazon Q DeveloperAmazon Q Developer is an AI-powered assistant for coding and AWS service guidance, not a service for hosting or providing foundation models.

Option B: Amazon BedrockThis is the correct answer. Amazon Bedrock provides access to foundation models, making it the primary service for building and scaling generative AI applications.

Option C: Amazon KendraAmazon Kendra is an intelligent search service powered by machine learning, not a service for providing foundation models or building generative AI applications.

Option D: Amazon ComprehendAmazon Comprehend is an NLP service for text analysis tasks like sentiment analysis, not for providing foundation models or supporting generative AI.