AWS Certified Cloud Practitioner
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A company wants to build an AI assistant capable of generating text, answering questions, and producing high-quality images. They prefer fully managed infrastructure, no model hosting, and light prompt-based customization rather than full fine-tuning. Which AWS service setup best meets these requirements?
Real Exam
Community
RRitesh
A
Use Amazon Rekognition for images and SageMaker for text generation
B
Use Amazon Bedrock with pre-trained foundation models and apply prompt-based customization
C
Deploy open-source models on EC2 GPU instances and apply custom fine-tuning
D
Use Amazon Lex for all text and image tasks
Explanation:
Explanation
Amazon Bedrock is the correct choice because:
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Fully Managed Infrastructure: Amazon Bedrock is a fully managed service that provides access to foundation models without requiring infrastructure management.
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No Model Hosting Required: With Bedrock, AWS hosts the models, eliminating the need for customers to deploy and manage their own model infrastructure.
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Prompt-Based Customization: Bedrock supports prompt engineering and light customization through techniques like prompt tuning, which aligns with the requirement for "light prompt-based customization rather than full fine-tuning."
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Multi-Modal Capabilities: Bedrock offers access to various foundation models that can handle text generation, question answering, and image generation tasks through a single service.
Why other options are incorrect:
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Option A: Amazon Rekognition is primarily for image and video analysis (not generation), and SageMaker requires more infrastructure management and is better suited for custom model training/deployment.
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Option C: EC2 GPU instances require significant infrastructure management, model hosting, and full fine-tuning capabilities, which contradicts the requirements.
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Option D: Amazon Lex is designed for conversational interfaces (chatbots) and cannot generate images or perform advanced text generation tasks.
Amazon Bedrock provides the ideal balance of managed infrastructure, access to state-of-the-art foundation models, and light customization capabilities through prompt engineering.
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