A company has fine-tuned an Amazon Bedrock foundation model (FM) to produce short document summaries.The company wants an automated metric that compares each model-generated summary with its human-written reference summary.Which metric will meet these requirements?
Answer(s): B
Recall-Oriented Understudy for Gisting Evaluation is used to evaluate generated text summaries by comparing them with human-written reference summaries. It measures overlap in words or sequences, making it suitable for automated summary quality evaluation.
A company is training a foundation model (FM). The company wants the FM training data to be well managed,secure, and compliant throughout the data lifecycle. The data must follow governance practices.Which option is an AWS data governance strategy for managing data across the data lifecycle?
Answer(s): D
Establishing data lifecycle policies, access controls, logging, and monitoring helps ensure that training data is managed securely, governed properly, and kept compliant throughout its lifecycle.
A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns.The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.Which solution meets these requirements?
Answer(s): C
Creating effective prompts helps guide the pre-trained generative AI model to produce content that aligns with the company's brand voice and messaging. The other options either involve model architecture changes or require extensive training, which are not necessary for aligning content generation.
A company is developing a product recommendation application by using a generative AI model. The company must minimize the application’s environmental impact.Which solution will meet these requirements?
Answer(s): A
Optimizing the model architecture for computational efficiency reduces the compute resources and energy required during inference, which directly lowers the environmental impact of running the generative AIapplication.
A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files.Which solution meets these requirements MOST cost-effectively?
Using an Amazon Bedrock knowledge base allows the model to efficiently access relevant information from thePDF manuals when needed, reducing the cost compared to continuously fine-tuning a model or providing allPDFs as context in each prompt. This approach ensures that only necessary context is provided, making it cost-effective.
Post your Comments and Discuss Amazon AIF-C01 exam prep with other Community members: