Practice Free AIF-C01 Exam Online Questions
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?
- A . Optimize the model’s architecture and hyperparameters to improve the model’s overall performance.
- B . Increase the model’s complexity by adding more layers to the model’s architecture.
- C . Create effective prompts that provide clear instructions and context to guide the model’s generation.
- D . Select a large, diverse dataset to pre-train a new generative model.
A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?
- A . Topic modeling
- B . Clustering models
- C . Prescriptive ML models
- D . BERT-based models
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.
Which solution meets these requirements?
- A . Build an automatic named entity recognition system.
- B . Create a recommendation engine.
- C . Develop a summarization chatbot.
- D . Develop a multi-language translation system.
An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.
What should the firm do when developing and deploying the LLM? (Select TWO.)
- A . Include fairness metrics for model evaluation.
- B . Adjust the temperature parameter of the model.
- C . Modify the training data to mitigate bias.
- D . Avoid overfitting on the training data.
- E . Apply prompt engineering techniques.
Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?
- A . Integration with Amazon S3 for object storage
- B . Support for geospatial indexing and queries
- C . Scalable index management and nearest neighbor search capability
- D . Ability to perform real-time analysis on streaming data
A company built a deep learning model for object detection and deployed the model to production.
Which AI process occurs when the model analyzes a new image to identify objects?
- A . Training
- B . Inference
- C . Model deployment
- D . Bias correction
A company is building a customer service chatbot. The company wants the chatbot to improve its responses by learning from past interactions and online resources.
Which AI learning strategy provides this self-improvement capability?
- A . Supervised learning with a manually curated dataset of good responses and bad responses
- B . Reinforcement learning with rewards for positive customer feedback
- C . Unsupervised learning to find clusters of similar customer inquiries
- D . Supervised learning with a continuously updated FAQ database
A company is building a solution to generate images for protective eyewear. The solution must have high accuracy and must minimize the risk of incorrect annotations.
Which solution will meet these requirements?
- A . Human-in-the-loop validation by using Amazon SageMaker Ground Truth Plus
- B . Data augmentation by using an Amazon Bedrock knowledge base
- C . Image recognition by using Amazon Rekognition
- D . Data summarization by using Amazon QuickSight
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
A company wants to make a chatbot to help customers. The chatbot will help solve technical problems without human intervention. The company chose a foundation model (FM) for the chatbot. The chatbot needs to produce responses that adhere to company tone.
Which solution meets these requirements?
- A . Set a low limit on the number of tokens the FM can produce.
- B . Use batch inferencing to process detailed responses.
- C . Experiment and refine the prompt until the FM produces the desired responses.
- D . Define a higher number for the temperature parameter.