Lesson 4.5 GANs Quiz

Lesson 4.5 GANs Quiz

10 Qs

quiz-placeholder

Similar activities

Y10 DGS - Computational Thinking Assessment

Y10 DGS - Computational Thinking Assessment

9th Grade

14 Qs

Nkti Ai Pretest

Nkti Ai Pretest

KG - University

10 Qs

Blockchain Quiz

Blockchain Quiz

Professional Development

10 Qs

Face Detection

Face Detection

KG - University

14 Qs

Graph and Tree Traversal

Graph and Tree Traversal

KG - University

15 Qs

Ch1_Excite: Introduction to AI

Ch1_Excite: Introduction to AI

KG - University

15 Qs

Laboratory Tools and Instruments

Laboratory Tools and Instruments

7th Grade

14 Qs

GD: Unit 4

GD: Unit 4

9th - 12th Grade

8 Qs

Lesson 4.5 GANs Quiz

Lesson 4.5 GANs Quiz

Assessment

Quiz

others

Medium

Created by

Nicholas Doblovosky

Used 3+ times

FREE Resource

10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

1. Generative AI systems can generate new content based on data provided to it.
True
False

2.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

2. Generative AI systems cannot create new images.
True
False

3.

MULTIPLE SELECT QUESTION

30 sec • 10 pts

3. Which of the following types of content can be created by generative AI systems? 
 (Select all correct answers.)
Text
Video
Images
Audio (sound)

4.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

4. GAN stands for “Generative Adversarial Network”
True
False

5.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

5. In a GAN there are two algorithms at work – one is a “generator” (that creates new content to show) and the other is a “discriminator” (that decides if the content it sees is fake or real).
True
False

6.

MULTIPLE CHOICE QUESTION

30 sec • 10 pts

6. If a generative AI system was never shown images of cats, it might have trouble generating new images of cats.
True
False

7.

MULTIPLE SELECT QUESTION

30 sec • 10 pts

7. Which of the following might happen if a GANs was trying to create a fake image of 
 Mount Everest? (Select all that are true)
The generator algorithm creates new images of mountains to show the discriminator.
The discriminator algorithm judges each mountain image the generator algorithm presents and decides if it is a fake (or not).
A discriminator algorithm gives feedback to the generator algorithm on why it thought it was a fake (so the generator can improve).
The GANS would just be able to read our minds, see the image of Mount Everest in our imaginations, and create it!

Create a free account and access millions of resources

Create resources
Host any resource
Get auto-graded reports
or continue with
Microsoft
Apple
Others
By signing up, you agree to our Terms of Service & Privacy Policy
Already have an account?