A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer. What should the company do to meet these requirements?
A. Evaluate the models by using built-in prompt datasets.
B. Evaluate the models by using a human workforce and custom prompt datasets.
C. Use public model leaderboards to identify the model.
D. Use the model InvocationLatency runtime metrics in Amazon CloudWatch when tryingmodels.
An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images. Which type of FM should the AI practitioner use to power the search application?
A. Multi-modal embedding model
B. Text embedding model
C. Multi-modal generation model
D. Image generation model
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model. The company needs to perform analysis on internal data and external data. Which solution will meet these requirements?
A. Store the data in Amazon S3. Create ML models and demand forecast predictions byusing Amazon SageMaker built-in algorithms that use the data from Amazon S3.
B. Import the data into Amazon SageMaker Data Wrangler. Create ML models anddemand forecast predictions by using SageMaker built-in algorithms.
C. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demandforecast predictions by using an Amazon Personalize Trending-Now recipe.
D. Import the data into Amazon SageMaker Canvas. Build ML models and demandforecast predictions by selecting the values in the data from SageMaker Canvas.
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive ornegative. Which prompt engineering strategy meets these requirements?
A. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.
B. Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.
C. Provide the new text passage to be classified without any additional context orexamples.
D. Provide the new text passage with a few examples of unrelated tasks, such as textsummarization or question answering.
Which metric measures the runtime efficiency of operating AI models?
A. Customer satisfaction score (CSAT)
B. Training time for each epoch
C. Average response time
D. Number of training instances
An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual humaneffort. Which strategy meets these requirements?
A. Object detection
B. Anomaly detection
C. Named entity recognition
D. Inpainting
A company has thousands of customer support interactions per day and wants to analyze these interactions to identify frequently asked questions and develop insights. Which AWS service can the company use to meet this requirement?
A. Amazon Lex
B. Amazon Comprehend
C. Amazon Transcribe
D. Amazon Translate
Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team's VPC?
A. Amazon Personalize
B. Amazon SageMaker JumpStart
C. PartyRock, an Amazon Bedrock Playground
D. Amazon SageMaker endpoints
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will successfully fine-tune the model?
A. Provide labeled data with the prompt field and the completion field.
B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csvformat.
C. Purchase Provisioned Throughput for Amazon Bedrock.
D. Train the model on journals and textbooks.
A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer. What can Amazon Q Developer do to help the company meet these requirements?
A. Create software snippets, reference tracking, and open-source license tracking.
B. Run an application without provisioning or managing servers.
C. Enable voice commands for coding and providing natural language search.
D. Convert audio files to text documents by using ML models.