AIF-C01 — questions

A real estate company is developing an ML model to predict house prices by using sales and marketing data. The company wants to use feature engineering to build a model that makes accurate predictions. Which approach will meet these requirements?

Which statement describes a generative AI use case for multimodal models?

Which term is the speed at which a pre-trained foundation model (FM) processes requests and delivers output?

A company is using a large collection of web data to produce a large language model (LLM). The company completes a random initialization of the model’s weights. Next, the company fits the model to the data through a language objective modelling function. Which stage of the model training process does this scenario describe?

A financial company is training a generative AI model to predict outcomes of loan applications. The training dataset is small. The dataset categorizes loan applicants as “younger-aged,” “middle-aged,” or “older-aged.” Most individuals in the dataset are characterized as "middle-aged." The company removes the age range feature from the training dataset. Which model behavior will likely happen as a result of this change to the dataset?

Sometimes generative AI models generate data unrelated to the input or the task. Which term is used for this disadvantage of using generative AI for business problems?

A company wants to deploy a secure AI system with controlled access. The system must allow only authorized personnel to access model training data. Which AWS service will meet these requirements?

A company plans to build an AI model for the company’s global customer base. The company wants to train the model on a dataset that reflects user diversity. Which action will meet this requirement?

A company wants to implement a single environment for both data and AI development. Developers across different teams must be able to access the environment and work together. The developers must be able to build and share models and generative AI applications securely in the environment. Which AWS solution will meet these requirements?

A company deploys a foundation model (FM). The company notices that the FM is producing answers to user-submitted questions about politics. The company wants to ensure that the model does not send answers to political questions to users. Which AWS solution will meet this requirement?

A company wants to use its documents as a knowledge base for a large language model (LLM) in a Retrieval Augmented Generation (RAG) solution. Which solution will meet these requirements?

Which AWS service creates business intelligence reports and automatically generates executive summaries based on data that users provide?

A company has developed a neural network model to replace an existing decision tree model. The neural network model has a higher prediction accuracy compared to the decision tree model. However, the neural network model’s decision process is not as explainable as the decision tree model’s decision process. Which tradeoff is the company making by adopting the neural network model?

A company is using a foundation model (FM) to generate creative marketing slogans for various products. The company wants to reuse a standard template with common instructions when generating slogans for different products. However, the company needs to add short descriptions for each product. Which Amazon Bedrock solution will meet these requirements?

Which outcome is a result of increasing model transparency?

A company wants to improve a large language model (LLM) for content moderation within 3 months. The company wants the model to moderate content according to the company's values and ethics. The LLM must also be able to handle emerging trends and new types of problematic content. Which solution will meet these requirements?

A company uses an Amazon Bedrock large language model (LLM) in an application. During testing, the company observes different outputs from the same input. What is the MOST likely cause of this issue?

A company is creating a model to label credit card transactions. The company has a large volume of sample transaction data to train the model. Most of the transaction data is unlabeled. The data does not contain confidential information. The company needs to obtain labeled sample data to fine-tune the model. Which solutions will meet these requirements? (Choose two.)

A company has developed an AI assistant application for customers by using Amazon Bedrock Agents. The company notices that the agents require additional context to make informed decisions consistently. The agents are not accessing external services to complete customer travel booking requests. The company needs to ensure that the agents access additional context when necessary. Which solution will meet this requirement?

A company has developed a generative AI application by using Amazon Bedrock. The application produces catalogs that are updated weekly. The company needs to select a pricing model for weekly catalog updates. Which Amazon Bedrock pricing model meets these requirements MOST cost-effectively?