AIF-C01 Free Practice Test

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?

1. A. Build an automatic named entity recognition system.
2. B. Create a recommendation engine.
3. C. Develop a summarization chatbot.
4. D. Develop a multi-language translation system.

Correct Answer: C
A summarization chatbot is ideal for extracting key points from legal documents. Large language models (LLMs) can be used to summarize complex texts, such as legal documents, making them more accessible and understandable.
✑ Option C (Correct): "Develop a summarization chatbot": This is the correct answer
because a summarization chatbot uses LLMs to condense and extract key information from text, which is precisely the requirement for reading and summarizing legal documents.
✑ Option A: "Build an automatic named entity recognition system" is incorrect
because it focuses on identifying specific entities, not summarizing documents.
✑ Option B: "Create a recommendation engine" is incorrect as it is used to suggest products or content, not summarize text.
✑ Option D: "Develop a multi-language translation system" is incorrect because translation is unrelated to summarizing text.
AWS AI Practitioner References:
✑ Using LLMs for Text Summarization on AWS: AWS supports developing summarization tools using its AI services, including Amazon Bedrock.

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?

1. A. Topic modeling
2. B. Clustering models
3. C. Prescriptive ML models
4. D. BERT-based models

Correct Answer: D
BERT-based models (Bidirectional Encoder Representations from Transformers) are suitable for tasks that involve understanding the context of words in a sentence and suggesting missing words. These models use bidirectional training, which considers the context from both directions (left and right of the missing word) to predict the appropriate word to fill in the gaps.
✑ BERT-based Models:
✑ Why Option D is Correct:
✑ Why Other Options are Incorrect:

A company has installed a security camera. The company uses an ML model to evaluate the security camera footage for potential thefts. The company has discovered that the model disproportionately flags people who are members of a specific ethnic group.
Which type of bias is affecting the model output?

1. A. Measurement bias
2. B. Sampling bias
3. C. Observer bias
4. D. Confirmation bias

Correct Answer: B
Sampling bias is the correct type of bias affecting the model output when it disproportionately flags people from a specific ethnic group.
✑ Sampling Bias:
✑ Why Option B is Correct:
✑ Why Other Options are Incorrect:

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?

1. A. Optimize the model's architecture and hyperparameters to improve the model's overall performance.
2. B. Increase the model's complexity by adding more layers to the model's architecture.
3. C. Create effective prompts that provide clear instructions and context to guide the model's generation.
4. D. Select a large, diverse dataset to pre-train a new generative model.

Correct Answer: C
Creating effective prompts is the best solution to ensure that the content generated by a pre-trained generative AI model aligns with the company's brand voice and messaging requirements.
✑ Effective Prompt Engineering:
✑ Why Option C is Correct:
✑ Why Other Options are Incorrect:

A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock.
What are the key benefits of using Amazon Bedrock agents that could help this retailer?

1. A. Generation of custom foundation models (FMs) to predict customer needs
2. B. Automation of repetitive tasks and orchestration of complex workflows
3. C. Automatically calling multiple foundation models (FMs) and consolidating the results
4. D. Selecting the foundation model (FM) based on predefined criteria and metrics

Correct Answer: B
Amazon Bedrock Agents provide the capability to automate repetitive tasks and orchestrate complex workflows using generative AI models. This is particularly beneficial for customer support inquiries, where quick and efficient processing is crucial.
✑ Option B (Correct): "Automation of repetitive tasks and orchestration of complex workflows": This is the correct answer because Bedrock Agents can automate common customer service tasks and streamline complex processes, improving response times and efficiency.
✑ Option A: "Generation of custom foundation models (FMs) to predict customer needs" is incorrect as Bedrock agents do not create custom models.
✑ Option C: "Automatically calling multiple foundation models (FMs) and consolidating the results" is incorrect because Bedrock agents focus on task automation rather than combining model outputs.
✑ Option D: "Selecting the foundation model (FM) based on predefined criteria and metrics" is incorrect as Bedrock agents are not designed for selecting models.
AWS AI Practitioner References:
✑ Amazon Bedrock Documentation: AWS explains that Bedrock Agents automate tasks and manage complex workflows, making them ideal for customer support automation.