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Generative AI Quiz

Authored by Suraj Singh

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Professional Development

Used 3+ times

Generative AI Quiz
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6 questions

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1.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

What is prompt engineering?

The process of developing and deploying generative AI models

The process of evaluating and improving generative AI models

The process of designing and testing prompts for generative AI models

The process of training and fine-tuning generative AI models

2.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

What is a prompt?

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

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

A feedback mechanism for a generative AI model to learn from

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

3.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

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

The length, specificity, and structure of the prompts

The domain, genre, and style of the prompts

The context, relevance, and novelty of the prompts

All the above

4.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

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

Teaching a model to transfer generated content between different domains

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

Transferring generated data to a separate physical device for storage

Transferring model parameters between different AI systems for collaborative tasks

5.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

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?

10 billion

3 billion

1.0 billion

175 billion

6.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

What are some tools or frameworks for prompt engineering?

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

PromptKit, PromptStudio, or PromptCraft

Hugging Face Transformers, PyTorch Lightning, or TensorFlow

All of the above

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