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Prompt Engineering for Generative AI

Total questions: 10

Worksheet time: 10mins

Name
Class
Date
1.

What is generative AI?

a)

A branch of artificial intelligence that focuses on creating new content or data

b)

A branch of artificial intelligence that focuses on analyzing existing content or data

c)

A branch of artificial intelligence that focuses on optimizing existing content or data

d)

A branch of artificial intelligence that focuses on learning from existing content or data

2.

What is prompt engineering?

a)

The process of developing and deploying generative AI models

b)

The process of evaluating and improving generative AI models

c)

The process of designing and testing prompts for generative AI models

d)

The process of training and fine-tuning generative AI models

3.

What is a prompt?

a)

A set of instructions or rules for a generative AI model to follow

b)

A piece of input or output for a generative AI model to process

c)

A feedback mechanism for a generative AI model to learn from

d)

A combination of input, output, and instructions for a generative AI model to process

4.

What are some examples of generative AI applications?

a)

Text summarization, image captioning, speech synthesis, style transfer, etc.

b)

Text generation, image synthesis, speech translation, face synthesis, etc.

c)

Text classification, image recognition, speech recognition, sentiment analysis, etc.

d)

Text translation, image segmentation, speech enhancement, face detection, etc.

5.

What are some challenges or limitations of generative AI?

a)

Data quality, model complexity, ethical issues, evaluation metrics, etc.

b)

Data availability, model robustness, legal issues, user feedback, etc.

c)

Data diversity, model scalability, social issues, user satisfaction, etc.

6.

What are some types of prompts for generative AI models?

a)

Textual, visual, audio, or multimodal prompts

b)

Open-ended, closed-ended, or multiple-choice prompts

c)

Direct, indirect, or implicit prompts

7.

What are some factors that affect the quality and performance of prompts for generative AI models?

a)

The length, specificity, and structure of the prompts

b)

The domain, genre, and style of the prompts

c)

The context, relevance, and novelty of the prompts

d)

All the Above

8.

What are some tools or frameworks for prompt engineering?

a)

PromptKit, PromptStudio, or PromptCraft

b)

GPT-3 Playground, OpenAI Codex, or DALL-E

c)

Hugging Face Transformers, PyTorch Lightning, or TensorFlow

d)

All of the above

9.

In the context of generative AI, what is the term "transfer learning" commonly associated with?

a)

Teaching a model to transfer generated content between different domains

b)

Training a model on a wide range of tasks and then fine-tuning it for a specific task

c)

Transferring generated data to a separate physical device for storage

d)

Transferring model parameters between different AI systems for collaborative tasks

10.

Generative AI models like GPT-3 have evolved over time in terms of scale. How many parameters does GPT-3 have, making it one of the largest language models as of my last update in September 2021?

a)
175 billion
b)

1.0 billion

c)
3 billion
d)
10 billion