Amazon AIF-C01 Online Practice Questions and Exam Preparation

Amazon AIF-C01 Online Questions & Answers

• Question 171:

  A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology.

  Which solution meets these requirements?

  A. Generative pre-trained transformers (GPT)
  B. Residual neural network
  C. Support vector machine
  D. WaveNet
  A. Generative pre-trained transformers (GPT)

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  Generative Pre-trained Transformers (GPT) are suitable for building an AI-based application that can generate SQL queries from natural language input provided by employees.

• Question 172:

  A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions. Which business objective should the company use to evaluate the effect of the LLM chatbot?

  A. Website engagement rate
  B. Average call duration
  C. Corporate social responsibility
  D. Regulatory compliance
  B. Average call duration

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  The business objective to evaluate the effect of an LLM chatbot aimed at reducing the actions required by call center employees should beaverage call duration.

• Question 173:

  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
  B. Text generation

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  Text generation is the feature of large language models (LLMs) that enables them to produce text based on a given prompt or input. In this scenario, the input would be natural language code comments, and the LLM would generate code based on those comments. This process involves understanding the context of the comment and generating corresponding code, which is the core functionality of text generation.

• Question 174:

  A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level. Which solution will meet these requirements?

  A. Decrease the batch size.
  B. Increase the epochs.
  C. Decrease the epochs.
  D. Increase the temperature parameter.
  B. Increase the epochs.

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  Increasing the number of epochs during model training allows the model to learn from the data over more iterations, potentially improving its accuracy up to a certain point. This is a common practice when attempting to reach a specific level of accuracy.

  Option B (Correct): "Increase the epochs":This is the correct answer because increasing epochs allows the model to learn more from the data, which can lead to higher accuracy.

  Option A:"Decrease the batch size" is incorrect as it mainly affects training speed and may lead to overfitting but does not directly relate to achieving a specific accuracy level.

  Option C:"Decrease the epochs" is incorrect as it would reduce the training time, possibly preventing the model from reaching the desired accuracy.

  Option D:"Increase the temperature parameter" is incorrect because temperature affects the randomness of predictions, not model accuracy.

  References:

  Model Training Best Practices on AWS:AWS suggests adjusting training parameters, like the number of epochs, to improve model performance.

• Question 175:

  A company is creating an agent for its application by using Amazon Bedrock Agents. The agent is performing well, but the company wants to improve the agent's accuracy by providing some specific examples. Which solution meets these requirements?

  A. Modify the advanced prompts for the agent to include the examples.
  B. Create a guardrail for the agent that includes the examples.
  C. Use Amazon SageMaker Ground Truth to label the examples.
  D. Run a script in AWS Lambda that adds the examples to the training dataset.
  A. Modify the advanced prompts for the agent to include the examples.

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  Embedding specific input-output examples directly into the agent's advanced prompt (few-shot prompting) guides the model toward more accurate behavior without retraining or additional tooling.

• Question 176:

  Which option describes embeddings in the context of AI?

  A. A method for compressing large datasets
  B. An encryption method for securing sensitive data
  C. A method for visualizing high-dimensional data
  D. A numerical method for data representation in a reduced dimensionality space
  D. A numerical method for data representation in a reduced dimensionality space

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  Embeddings are numerical representations of data, such as words, images, or items, in a lower- dimensional vector space. They capture semantic relationships and patterns in the data, enabling models to process and compare inputs efficiently.

• Question 177:

  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. Interpretability
  B. Hallucinations
  C. Data bias
  D. Nondeterminism
  B. Hallucinations

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  Explanation

  Hallucinations refer to cases where a generative AI model produces outputs that are incorrect, irrelevant, or not grounded in the input or real data.

• Question 178:

  A company needs to monitor the performance of its ML systems by using a highly scalable AWS service. Which AWS service meets these requirements?

  A. Amazon CloudWatch
  B. AWS CloudTrail
  C. AWS Trusted Advisor
  D. AWS Config
  A. Amazon CloudWatch

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  Amazon CloudWatch is a highly scalable AWS service designed for monitoring and observability. It provides real-time monitoring of system metrics, including performance data for ML systems, such as resource utilization (CPU, memory, etc.), model inference latency, request counts, and errors. CloudWatch enables users to set up alarms, visualize metrics, and automate actions based on performance thresholds, making it ideal for monitoring the performance of ML systems.

• Question 179:

  A company stores its AI datasets in Amazon S3 buckets. The company wants to share the S3 buckets with its business partners. The company needs to avoid accidentally sharing sensitive data.

  Which AWS service should the company use to discover sensitive data in the dataset?

  A. Amazon Kendra
  B. Amazon Macie
  C. Amazon Textract
  D. AWS Data Exchange
  B. Amazon Macie

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  Explanation

  Amazon Macie automatically discovers, classifies, and protects sensitive data in Amazon S3 using machine learning, enabling the company to identify sensitive information before sharing datasets with business partners.

• Question 180:

  An AI practitioner notices a large language model (LLM) is generating different responses for the same input across multiple invocations. Which risk of AI does this describe?

  A. Hallucinations
  B. Nondeterminism
  C. Accuracy
  D. Multimodality
  B. Nondeterminism

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  Nondeterminism refers to the property where a large language model generates different responses for the same input due to inherent randomness or stochasticity in the generation process. This can lead to varying outputs on multiple invocations with identical inputs.