Practice artificial-intelligence Quizzes

Master artificial-intelligence with simple, engaging quizzes designed to make learning fun and productive. Whether preparing for exams or revising core concepts, these quizzes offer instant results, clear explanations and a structured way to build confidence and strengthen your foundation.

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Learn artificial-intelligence step by step with interactive quizzes designed for beginners and learners revising key concepts. Build a strong foundation with clear, structured practice in artificial-intelligence.

Question 1

What is the primary goal of Artificial Intelligence?

To develop systems that simulate human intelligence processes

To enhance computer processing speeds

To create systems that require human input to operate

To replace all jobs currently performed by humans

Question 2

What is the difference between Narrow AI and General AI?

Narrow AI performs specific tasks

Narrow AI has the capability to perform any intellectual task

General AI performs specific tasks

General AI is currently in widespread use

Question 3

Which of the following best describes Narrow AI?

It is designed to perform specific tasks.

It can learn and adapt like a human.

It has human-like reasoning and understanding.

It can perform any intellectual task that humans can.

Question 4

Which of the following is a characteristic of General AI?

It can not learn and adapt.

It is capable of solving problems outside its pre-programmed tasks.

It can only perform one specific task.

It is widely used in real-world applications.

Question 5

Which of the following is an example of Narrow AI?

A robot that can clean your house autonomously

An AI that can think and reason like a human

An AI system that can play chess at a world-class level

A machine that can understand and process all human languages

Question 6

What is supervised learning?

Learning without labeled data

Learning with labeled data

A method where machines learn by trial and error

A method that requires no human interaction

Question 7

Which statement best differentiates Narrow AI and General AI?

General AI can solve specific problems, while Narrow AI can solve any intellectual problem.

Narrow AI is designed for a specific task, while General AI can handle any task like a human.

General AI is currently widely used, whereas Narrow AI is still theoretical.

Narrow AI can only be used for games, while General AI is used for real-world applications.

Question 8

In which year was the term "Artificial Intelligence" first coined?

1960

1945

1956

1995

Question 9

Which of the following is NOT a type of AI as defined by capabilities?

General AI

Super AI

Narrow AI

Supervised AI

Question 10

Which of the following is an example of General AI?

IBM's Watson

Siri

Google's AlphaGo

None of the above

Question 11

In Python, which library is commonly used for AI tasks such as Natural Language Processing (NLP)?

Pandas

NLTK

NumPy

SciPy

Question 12

Your AI system is making decisions based on incorrect historical data. What is the most likely cause?

Lack of data

Algorithm complexity

Overfitting

Data bias

Question 13

What is the first step in the problem-solving process in AI?

Develop an algorithm

Test the solution

Define the problem

Implement the solution

Question 14

Which AI technique involves breaking down a problem into smaller sub-problems?

Heuristic search

Greedy algorithm

Depth-first search

Divide and conquer

Question 15

What is the primary purpose of using a search algorithm in AI problem-solving?

To systematically explore possible actions to reach a goal

To randomly select possible solutions

To enhance the graphical display of the system

To store large datasets efficiently

Question 16

Which of the following is a disadvantage of using brute force search in AI?

It is computationally expensive

It requires domain-specific knowledge

It is not guaranteed to find a solution

It only works for small datasets

Question 17

What role does backtracking play in AI problem-solving?

It simplifies the problem

It guarantees finding the optimal solution

It avoids revisiting already explored paths

It is used to store solutions

Question 18

Which Python library can be used to visualize search algorithms applied to a problem?

matplotlib

Scikit-learn

TensorFlow

Pandas

Question 19

Which of the following would be considered an ethical concern in AI?

High-dimensional feature extraction

Black-box model interpretation

Algorithmic bias in decision-making

Low generalization error

Question 20

What is "catastrophic forgetting" in the context of neural networks?

Model convergence to a suboptimal solution

Forgetting old knowledge when learning new information

Loss of weights due to vanishing gradients

Overfitting to noise in training data

Question 21

The name of the Artificial Intelligence system developed by Daniel Bobrow was?

BACON

SIMD

STUDENT

None of the above

Question 22

Which of the following are appropriate levels for a knowledge-based AI agent?

Knowledge Level

Logical Level

Implementation Level

All of the above

Question 23

Which of the following are informed search methods?

Best First Search

A* Search

Memory Bound Heuristic Search

All of the above

Question 24

Which of the following are valid 3D image processing techniques?

Motion

Texture

Contour

All of the above

Question 25

Which of the following is not an application of artificial intelligence?

Natural Language Processing

Digital Assistants

Computer Vision

Database Management System

Question 26

Which of the following is the common language for Artificial Intelligence?

Python

Java

Lisp

Question 27

Which of the following search method takes less memory space?

Optimal Search

Depth First Search

Linear Search

Best First Search

Question 28

Which of the following symbols in AI are logical symbols?

Negation

Conjunction

Implication

All of the above

Question 29

What is the primary purpose of a loss function in machine learning?

To visualize the training process

To optimize hyperparameters

To increase dataset size

To measure how well a model is performing

Question 30

How would you implement the A* search algorithm for pathfinding in a graph?

Use a simple list to store nodes

Use a priority queue to store nodes

Use recursion to explore all paths

Use a stack to store nodes