Exam C PDF

Exam C QUESTION 1 Which prompting attack directly exposes the configured behavior of a large language model (LLM)? A. Prompted persona switches B. Exploiting friendliness and trust C. Ignoring the prompt template D. Extracting the prompt template Answer: D QUESTION 2 A company wants to use Amazon...

Exam C QUESTION 1 Which prompting attack directly exposes the configured behavior of a large language model (LLM)? A. Prompted persona switches B. Exploiting friendliness and trust C. Ignoring the prompt template D. Extracting the prompt template Answer: D QUESTION 2 A company wants to use Amazon Bedrock. The company needs to review which security aspects the company is responsible for when using Amazon Bedrock. Which security aspect will the company be responsible for? A. Patching and updating the versions of Amazon Bedrock B. Protecting the infrastructure that hosts Amazon Bedrock C. Securing the company's data in transit and at rest D. Provisioning Amazon Bedrock within the company network Answer: C QUESTION 3 A social media company wants to use a large language model (LLM) to summarize messages. The company has chosen a few LLMs that are available on Amazon SageMaker JumpStart. The company wants to compare the generated output toxicity of these models. Which strategy gives the company the ability to evaluate the LLMs with the LEAST operational overhead? A. Crowd-sourced evaluation B. Automatic model evaluation C. Model evaluation with human workers D. Reinforcement learning from human feedback (RLHF) Answer: B QUESTION 4 A company is testing the security of a foundation model (FM). During testing, the company wants to get around the safety features and make harmful content. Which security technique is this an example of? A. Fuzzing training data to find vulnerabilities B. Denial of service (DoS) C. Penetration testing with authorization D. Jailbreak Answer: D QUESTION 5 A company needs to use Amazon SageMaker for model training and inference. The company must comply with regulatory requirements to run SageMaker jobs in an isolated environment without internet access. Which solution will meet these requirements? A. Run SageMaker training and inference by using SageMaker Experiments. B. Run SageMaker training and Inference by using network Isolation. C. Encrypt the data at rest by using encryption for SageMaker geospatial capabilities. D. Associate appropriate AWS Identity and Access Management (IAM) roles with the SageMaker jobs. Answer: B QUESTION 6 An ML research team develops custom ML models. The model artifacts are shared with other teams for integration into products and services. The ML team retains the model training code and data. The ML team wants to build a mechanism that the ML team can use to audit models. Which solution should the ML team use when publishing the custom ML models? A. Create documents with the relevant information. Store the documents in Amazon S3. B. Use AWS AI Service Cards for transparency and understanding models. C. Create Amazon SageMaker Model Cards with intended uses and training and inference details. D. Create model training scripts. Commit the model training scripts to a Git repository. Answer: C QUESTION 7 A software company builds tools for customers. The company wants to use AI to increase software development productivity. Which solution will meet these requirements? A. Use a binary classification model to generate code reviews. B. Install code recommendation software in the company's developer tools. C. Install a code forecasting tool to predict potential code issues. D. Use a natural language processing (NLP) tool to generate code. Answer: B QUESTION 8 A retail store wants to predict the demand for a specific product for the next few weeks by using the Amazon SageMaker DeepAR forecasting algorithm. Which type of data will meet this requirement? A. Text data B. Image data C. Time series data D. Binary data Answer: C QUESTION 9 A large retail bank wants to develop an ML system to help the risk management team decide on loan allocations for different demographics. What must the bank do to develop an unbiased ML model? A. Reduce the size of the training dataset. B. Ensure that the ML model predictions are consistent with historical results. C. Create a different ML model for each demographic group. D. Measure class imbalance on the training dataset. Adapt the training process accordingly. Answer: D QUESTION 10 Which prompting technique can protect against prompt injection attacks? A. Adversarial prompting B. Zero-shot prompting C. Least-to-most prompting D. Chain-of-thought prompting Answer: A QUESTION 11 A company has fine-tuned a large language model (LLM) to answer questions for a help desk. The company wants to determine if the fine-tuning has enhanced the model's accuracy. Which metric should the company use for the evaluation? A. Precision B. Time to first token C. F1 score D. Word error rate Answer: C QUESTION 12 A company is using Retrieval Augmented Generation (RAG) with Amazon Bedrock and Stable Diffusion to generate product images based on text descriptions. The results are often random and lack specific details. The company wants to increase the specificity of the generated images. Which solution meets these requirements? A. Increase the number of generation steps. B. Use the MASK_IMAGE_BLACK mask source option. C. Increase the classifier-free guidance (CFG) scale. D. Increase the prompt strength. Answer: C QUESTION 13 A company wants to implement a large language model (LLM) based chatbot to provide customer service agents with real-time contextual responses to customers' inquiries. The company will use the company's policies as the knowledge base. Which solution will meet these requirements MOST cost-effectively? A. Retrain the LLM on the company policy data. B. Fine-tune the LLM on the company policy data. C. Implement Retrieval Augmented Generation (RAG) for in-context responses. D. Use pre-training and data augmentation on the company policy data. Answer: C QUESTION 14 A company wants to create a new solution by using AWS Glue. The company has minimal programming experience with AWS Glue. Which AWS service can help the company use AWS Glue? A. Amazon Q Developer B. AWS Config C. Amazon Personalize D. Amazon Comprehend Answer: A QUESTION 15 A company is developing a mobile ML app that uses a phone's camera to diagnose and treat insect bites. The company wants to train an image classification model by using a diverse dataset of insect bite photos from different genders, ethnicities, and geographic locations around the world. Which principle of responsible Al does the company demonstrate in this scenario? A. Fairness B. Explainability C. Governance D. Transparency Answer: A QUESTION 16 A company is developing an ML model to make loan approvals. The company must implement a solution to detect bias in the model. The company must also be able to explain the model's predictions. Which solution will meet these requirements? A. Amazon SageMaker Clarify B. Amazon SageMaker Data Wrangler C. Amazon SageMaker Model Cards D. AWS AI Service Cards Answer: A QUESTION 17 A company has developed a generative text summarization model by using Amazon Bedrock. The company will use Amazon Bedrock automatic model evaluation capabilities. Which metric should the company use to evaluate the accuracy of the model? A. Area Under the ROC Curve (AUC) score B. F1 score C. BERTScore D. Real world knowledge (RWK) score Answer: C QUESTION 18 An Al practitioner wants to predict the classification of flowers based on petal length, petal width, sepal length, and sepal width. Which algorithm meets these requirements? A. Kneest neighbors (k-NN) B. K-mean C. Autoregressive Integrated Moving Average (ARIMA) D. Linear regression Answer: A QUESTION 19 A company is using custom models in Amazon Bedrock for a generative Al application. The company wants to use a company managed encryption key to encrypt the model artifacts that the model customization jobs create. Which AWS service meets these requirements? A. AWS Key Management Service (AWS KMS B. Amazon Inspector C. Amazon Macie D. AWS Secrets Manager Answer: A QUESTION 20 A company wants to use large language models (LLMs) to produce code from natural language code comments. Which LLM feature meets these requirements? A. Text summarization B. Text generation C. Text completion D. Text classification Answer: B QUESTION 21 A company is introducing a mobile app that helps users learn foreign languages. The app makes text more coherent by calling a large language model (LLM). The company collected a diverse dataset of text and supplemented the dataset with examples of more readable versions. The company wants the LLM output to resemble the provided examples. Which metric should the company use to assess whether the LLM meets these requirements? A. Value of the loss function B. Semantic robustness C. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) score D. Latency of the text generation Answer: C QUESTION 22 A company notices that its foundation model (FM) generates images that are unrelated to the prompts. The company wants to modify the prompt techniques to decrease unrelated images. Which solution meets these requirements? A. Use zero-shot prompts. B. Use negative prompts. C. Use positive prompts. D. Use ambiguous prompts. Answer: B QUESTION 23 A company wants to use a large language model (LLM) to generate concise, feature-specific descriptions for the company's products. Which prompt engineering technique meets these requirements? A. Create one prompt that covers all products. Edit the responses to make the responses more specific, concise, and tailored to each product. B. Create prompts for each product category that highlight the key features. Include the desired output format and length for each prompt response. C. Include a diverse range of product features in each prompt to generate creative and unique descriptions. D. Provide detailed, product-specific prompts to ensure precise and customized descriptions. Answer: B QUESTION 24 A company is developing an ML model to predict customer churn. The model performs well on the trainins dataset but does not accurately predict churn for new data. Which solution will resolve this issue? A. Decrease the regularization parameter to increase model complexity. B. Increase the regularization parameter to decrease model complexity. C. Add more features to the input data. D. Train the model for more epochs. Answer: B QUESTION 25 A company is implementing intelligent agents to provide conversational search experiences for its customers. The company needs a database service that will support storage and queries of embeddings from a generative Al model as vectors in the database. Which AWS service will meet these requirements? A. Amazon Athena B. Amazon Aurora PostgreSQL C. Amazon Redshift D. Amazon EMR Answer: B QUESTION 26 A financial institution is building an AI solution to make loan approval decisions by using a foundation model (FM). For security and audit purposes, the company needs the Al solution's decisions to be explainable. Which factor relates to the explainability of the Al solution's decisions? A. Model complexity B. Training time C. Number of hyperparameters D. Deployment time Answer: A QUESTION 27 A pharmaceutical company wants to analyze user reviews of new medications and provide a concise overview for each medication. Which solution meets these requirements? A. Create a time-series forecasting model to analyze the medication reviews by using Amazon Personalize. B. Create medication review summaries by using Amazon Bedrock large language models (LLMS). C. Create a classification model that categorizes medications into different groups by using Amazon SageMaker. D. Create medication review summaries by using Amazon Rekognition. Answer: B QUESTION 28 A company wants to build a lead prioritization application for its employees to contact potential customers. The application must give employees the ability to view and adjust the weights assigned to different var- iables in the model based on domain knowledge and expertise. Which ML model type meets these requirements? A. Logistic regression model B. Deep learning model built on principal components C. K-nearest neighbors (k-NN) model D. Neural network Answer: A QUESTION 29 Which strategy will determine if a foundation model (FM) effectively meets business objectives? A. Evaluate the model's performance on benchmark datasets. B. Analyze the model's architecture and hyperparameters. C. Assess the model's alignment with specific use cases. D. Measure the computational resources required for model deployment. Answer: C QUESTION 30 A company needs to train an ML model to classify images of different types of animals. The company has a large dataset of labeled images and will not label more data. Which type of learning should the company use to train the model? A. Supervised learning B. Unsupervised learning C. Reinforcement learning D. Active learning Answer: A QUESTION 31 Which phase of the ML lifecycle determines compliance and regulatory requirements? A. Feature engineering B. Model training C. Data collection D. Business goal identification Answer: D QUESTION 32 A food service company wants to develop an ML model to help decrease daily food waste and increase sales revenue. The company needs to continuously improve the model's accuracy. Which solution meets these requirements? A. Use Amazon SageMaker and iterate with newer data. B. Use Amazon Personalize and iterate with historical data. C. Use Amazon CloudWatch to analyze customer orders. D. Use Amazon Rekognition to optimize the model. Answer: A QUESTION 33 A company has developed an ML model to predict real estate sale prices. The company wants to deploy the model to make predictions without managing servers or infrastructure. Which solution meets these requirements? A. Deploy the model on an Amazon EC2 instance. B. Deploy the model on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. C. Deploy the model by using Amazon CloudFront with an Amazon S3 integration. D. Deploy the model by using an Amazon SageMaker endpoint. Answer: D QUESTION 34 A company wants to develop an Al application to help its employees check open customer claims, identify details for a specific claim, and access documents for a claim. Which solution meets these requirements? A. Use Agents for Amazon Bedrock with Amazon Fraud Detector to build the application. B. Use Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build the application. C. Use Amazon Personalize with Amazon Bedrock knowledge bases to build the application. D. Use Amazon SageMaker to build the application by training a new ML model. Answer: B QUESTION 35 A manufacturing company uses Al to inspect products and find any damages or defects. Which type of Al application is the company using? A. Recommendation system B. Natural language processing (NLP) C. Computer vision D. Image processing Answer: C QUESTION 36 A company wants to create an ML model to predict customer satisfaction. The company needs fully automated model tuning. Which AWS service meets these requirements? A. Amazon Personalize B. Amazon SageMaker C. Amazon Athena D. Amazon Comprehend Answer: B QUESTION 37 Which technique can a company use to lower bias and toxicity in generative Al applications during the Postprocessing ML lifecycle? A. Human-in-the-loop B. Data augmentation C. Feature engineering D. Adversarial training Answer: A QUESTION 38 A bank has fine-tuned a large language model (LLM) to expedite the loan approval process. During an external audit of the model, the company discovered that the model was approving loans at a faster pace for a specific demographic than for other demographics. How should the bank fix this issue MOST cost-effectively? A. Include more diverse training data. Fine-tune the model again by using the new data. B. Use Retrieval Augmented Generation (RAG) with the fine-tuned model. C. Use AWS Trusted Advisor checks to eliminate bias. D. Pre-train a new LLM with more diverse training data. Answer: A QUESTION 39 A company needs to log all requests made to its Amazon Bedrock API. The company must retain the logs securely for 5 years at the lowest possible cost. Which combination of AWS service and storage class meets these requirements? (Choose two.) A. AWS CloudTrail B. Amazon CloudWatch C. AWS Audit Manager D. Amazon S3 Intelligent-Tiering E. Amazon S3 Standard Answer: AD