ENABLERS OF ARTIFICAL INTELLIGENCE /Machine Learning

Question 2

What is human compatible AI?

Answer 2

AI systems designed to align with human values, goals, and ethical principles to remain safe, beneficial, and controllable.

Question 3

Give an example of human compatible AI in practice.

Answer 3

Adaptive cruise control.

Question 4

What is wearable AI?

Answer 4

Devices that combine AI with wearable technology to provide functionalities like health monitoring and assistance.

Question 5

Give two examples of wearable AI devices.

Answer 5

Smart watches, fitness trackers.

Question 6

What is Edge AI?

Answer 6

Deployment of AI on local devices rather than relying on centralized cloud computing, allowing real-time processing and better privacy.

Question 7

Give two examples of Edge AI devices.

Answer 7

Smartphones, autonomous vehicles.

Question 8

How does AI enhance the Internet of Things (IoT)?

Answer 8

By improving functionality, efficiency, and decision-making of connected devices across sectors.

Question 9

List three IoT applications enhanced by AI.

Answer 9

Smart homes, agriculture, healthcare.

Question 10

What is a robot?

Answer 10

A programmable machine capable of carrying out tasks autonomously or semi-autonomously.

Question 11

What are five types of AI robots?

Answer 11

Industrial, personal, autonomous, nanobots, humanoids.

Question 12

What is Robotic Process Automation (RPA)?

Answer 12

A technology that uses software bots to automate repetitive, rule-based tasks like data entry.

Question 13

What does it mean for an AI agent to be autonomous?

Answer 13

It learns and makes decisions independently without relying entirely on designer’s prior knowledge.

Question 14

What is machine learning?

Answer 14

The field concerned with creating programs that improve automatically through experience.

Question 15

What is deep learning?

Answer 15

A type of machine learning using multi-layered neural networks inspired by the human brain.

Question 16

Name three applications of deep learning.

Answer 16

Speech recognition, image recognition, NLP.

Question 17

What are the three main types of machine learning?

Answer 17

Supervised, unsupervised, reinforcement.

Question 18

What is supervised learning?

Answer 18

Training a model using labeled data to predict future labels.

Question 19

What is unsupervised learning?

Answer 19

Training a model without labeled data to discover hidden patterns.

Question 20

What is reinforcement learning?

Answer 20

Training a model using reward and punishment.

Question 21

What is online learning in ML?

Answer 21

Incremental learning using small batches of data, useful for changing data or limited hardware.

Question 22

What is instance-based learning?

Answer 22

Learning by heart with examples like times tables; uses similarity measures.

Question 23

What is model-based learning?

Answer 23

Building a predictive model from data, like fitting a line to make predictions.

Question 24

What is the role of hyperparameters in training?

Answer 24

They define how the model learns and affect the outcome.

Question 25

What is bias in machine learning?

Answer 25

The error from incorrect assumptions in the learning algorithm.

Question 26

What is variance in machine learning?

Answer 26

The model's sensitivity to fluctuations in the training data.

Question 27

List five common applications of machine learning.

Answer 27

Prediction, object recognition, classification, clustering, recommendation.

Question 28

Give an example of machine learning used in object recognition.

Answer 28

Autonomous vehicles recognizing pedestrians and traffic signs.

Question 29

Give an example of classification in ML.

Answer 29

Spam email detection.

Question 30

What is clustering in ML?

Answer 30

Grouping data into segments based on similarity, such as customer segmentation.

Question 31

What is a recommendation system in ML?

Answer 31

Suggesting products or content based on user behavior and preferences.