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Generative AI

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

What is Machine Learning (ML)?

a)

A branch of AI focused on building systems that learn from data

b)

A method for programming computers to solve complex problems

c)

A technology that allows machines to mimic human actions

d)

A framework for designing neural networks

2.

What is Deep Learning (DL)?

a)


A subset of machine learning involving neural networks with multiple layers

b)

A method for processing big data in real-time

c)

A type of machine learning focused on natural language processing

d)

A machine learning technique that requires little data

3.

What is Generative AI (GenAI)?

a)
Generative AI (GenAI) is a type of AI that only analyzes existing data without creating new content.
b)
Generative AI (GenAI) is a technology used solely for data storage and retrieval.
c)
Generative AI (GenAI) refers to AI systems that can only replicate existing content without any modifications.
d)
Generative AI (GenAI) is a type of AI that generates new content based on learned patterns from existing data.
4.

Explain the concept of 'AI ethics' and why it is important in the field of technology.

a)

AI ethics only applies to certain industries, not technology as a whole

b)

AI ethics is irrelevant in technology as long as the end goal is achieved

c)

AI ethics is crucial in technology to ensure fairness, transparency, and respect for human values in the development and use of artificial intelligence.

d)

AI ethics is a hindrance to technological progress and innovation

5.

What type of content has generative AI had the biggest impact on so far?

a)

Text generation

b)

Image generation

c)

Audio generation

d)

Video generation

6.

Which of the following is NOT a characteristic of Artificial Intelligence?

a)
Machine learning
b)
Natural language processing
c)
Robotics
d)
Emotional intelligence
7.

What can generative AI misuse lead to?

a)

Reduction in data usage

b)

Improved AI behavior

c)

Faster internet speeds

d)

Deepfakes

8.

What are some tools or frameworks for prompt engineering?

a)

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

b)

PromptKit, PromptStudio, or PromptCraft

c)

Hugging Face Transformers, PyTorch Lightning, or TensorFlow

d)

All of the above

9.

Who is he ?

b)

Sam Altman

c)

Sundar Pichai

d)

Andrew NG

10.

Which model is known for generating human-like text?

a)

CNN

b)

RNN

c)

GPT

d)

SVM

11.

What does GPT stand for in the context of Generative AI?

a)

General Purpose Transformer

b)

Generative Pre-trained Transformer

c)

General Pre-trained Transformer

d)

Generative Purpose Transformer

12.

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

13.

What is "zero-shot learning" in the context of Generative AI?

a)

Training a model without any data

b)

The ability to perform tasks without prior training on specific examples

c)

Fine-tuning a model with minimal data

d)

Generating data from scratch

14.

What is "few-shot learning" in the context of Generative AI?

a)

Training a model with a large amount of data

b)

The ability to learn from a few examples

c)

Generating data with minimal supervision

d)

Fine-tuning a model with extensive data

15.

Which of the following is an example of a Generative AI model for image generation?

a)

BERT

b)

GPT-3

c)

DALL-E

d)

GPT-5

16.

Which of the following is a popular dataset used for training language models?

a)

ImageNet

b)

COCO

c)

Wikipedia

d)

CIFAR-10

17.

What is a transformer in the context of AI?

a)

A transformer is a neural network architecture that uses self-attention mechanisms to process sequential data.

b)

A transformer is a type of physical device used for electrical energy conversion.

c)

A transformer is a programming language used for AI development.

d)

A transformer is a data storage system for large datasets.

18.

Explain the concept of self-attention in transformers.

a)

Self-attention is a method for translating text into images.

b)

Self-attention is a technique used only in convolutional neural networks.

c)

Self-attention refers to the process of ignoring all other words in a sequence.

d)

Self-attention is a mechanism in transformers that allows the model to weigh the importance of different words in a sequence based on their relationships.

19.

Which of the following is a common challenge in training large-scale language models?

a)

Overfitting on small datasets

b)

Managing long-range dependencies

c)

High computational cost

d)

Limited training data

20.

What is mentioned as the potential of language models in the lecture?

a)

Decreased accuracy

b)

Minimal impact

c)

Revolutionizing industries

d)

Limited applications