AWS Certified Cloud Practitioner

Explanation:

Amazon Bedrock's Model Customization (Fine-tuning) capability allows organizations to fine-tune foundation models like Amazon Titan on their proprietary data. This enables:

• Customization for specific use cases: Adapting models to understand domain-specific terminology, tone, and requirements

• Proprietary data training: Using company-specific data (like product catalogs, customer interactions, etc.) to improve model performance

• Tone and style adaptation: Adjusting the model's output to match the company's brand voice and communication style

Why other options are incorrect:

• B) Guardrails for Bedrock: This is for implementing safety controls and content filtering, not model customization

• C) Continued pretraining: While related to model training, this typically refers to ongoing training of base models, not fine-tuning for specific use cases

• D) Knowledge Bases: This is for connecting models to external data sources for retrieval-augmented generation, not for fine-tuning the model itself

Fine-tuning allows the e-commerce platform to make the Amazon Titan model more effective for their specific product catalog and desired communication style.