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AI Basic Concepts Quiz

Total questions: 36

Worksheet time: 28mins

Name
Class
Date
1.

What is Artificial intelligence?

a)

When robots take over the world

b)

Ability of a program or machine to think and learn

c)

Ability of a program or machine to depend on human

d)

None of the above

2.

Intelligent machines that can learn any tasks that humans can do.

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

3.

Can be defined as the ability of a computer to perform tasks that require human intelligence.

a)

Machine Learning

b)

Artificial Intelligence

c)

Unsupervised Learning

4.

A machine that is specialized in one task or area.

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

5.

A theoretical type of AI where the machine can outperform human intelligence in every task

a)

Artificial general intelligence

b)

Artificial narrow intelligence

c)

Artificial super intelligence

6.

The ability of a computer to understand images and videos

a)

Robotics

b)

Natural Language Processing

c)

Computer Vision

7.

The ability of a computer to understand human language is called

a)

NLP

b)

Computer Vision

c)

Medical Science

8.

Human face recognition is considered as

a)

NLP

b)

Computer Vision

9.

Objects tracking is considered as

a)

NLP

b)

Computer vision

10.

Voice to text is considered as

a)

NLP

b)

Computer Vision

11.

The study of algorithms that enable the machine to learn from data and to make decisions without the help of humans.

a)

Machine Learning

b)

Artificial Intelligence

12.

learning from examples in a training data set is a

a)

Supervised Learning

b)

Unsupervised Learning

13.

The study of algorithms that enable the machine to learn from data and to make decisions without the help of humans.

a)

Machine Learning

b)

Artificial Intelligence

14.

When the machine will be provided with features only. It will then try to group objects with similar features

a)

Supervised Learning

b)

Unsupervised Learning

15.

The unique characteristics of something

a)

Supervised learning

b)

Features

c)

Unsupervised learning

16.

The unique characteristics of something

a)

Supervised learning

b)

Features

c)

Unsupervised learning

17.

If the computer is trained to recognize cars, bikes and trucks with a human supervision.

a)

Supervised Learning

b)

Unsupervised Learning

18.

Predict the price of a house

a)

Supervised Learning

b)

Unsupervised Learning

19.

Recommend a product based on your buying history

a)

Supervised Learning

b)

Unsupervised Learning

20.

Identify Currency

a)

Supervised Learning

b)

Unsupervised Learning

21.

(bonus q) Which numbers are part of binary?

a)

0 and 1

b)

1 and 2

c)

1 to 99

d)

1, 2 and 3

22.

How do we give instructions during programming?

a)

Coding

b)

Algorithm

c)

All of the above

d)

None of the above

23.

How does an AI device learn and think?

a)

It hacks our computer

b)

It accepts data and trains itself, then creates a model

c)

It hacks our brain

d)

None of the above

24.

What is data?

a)

Raw facts that may not make sense

b)

Information

c)

Data helps us to browse

d)

None of the above

25.

What is information?

a)

Information is processed data

b)

Information is data

c)

Information is something

d)

I do not know

26.

Which of these is NOT an AI technology

a)

Facial recognition

b)

Image recognition

c)

Robotics

d)

Animation

27.

Which of the following is not an example of Artificial Intelligence?

a)

Chess Playing Computers

b)

Self Driving Cars

c)

Face Recognising Devices

d)

Money Counting Machines

28.

Which one is NLP based application

a)

Google Lens

b)

Amazon Alexa

c)

Predictive analytical tools

29.

which one is Computer vision based application

a)

Apple Siri

b)

Text To Speech

c)

Google lens

30.

This device uses

a)

Machine Learning

b)

Deep Learning

c)

Predictive Analysis

31.

The technology used here is

a)

Machine Learning

b)

Deep Learning

c)

Predictive Analysis

32.

This type of application uses

a)

Deep Learning

b)

Machine Learning

c)

Predictive Analysis

33.

Deciding whether an email is spam or not:

a)

regression problem

b)

classification problem

c)

expert system

34.

Classification problem with machine learning from unlabelled instances, which are grouped in clusters that have close values for features:

a)

supervised learning

b)

unsupervised learning

c)

reinforcement learning

35.

Kind of learning in which a robot or software bot learns to make the right decisions to achieve a goal, over a great many different trials:

a)

supervised learning

b)

unsupervised learning

c)

reinforcement learning

36.

Which one of these is not an area of AI?

a)

computer vision/image recognition

b)

voice recognition

c)

web design

d)

robotics