AI Overview Glossary

Question 1

Machine Learning

Answer 1

A branch of AI that uses data and algorithms to make predictions or decisions.

Question 2

Artificial Intelligence

Answer 2

Software that imitates human behaviors and capabilities, such as reasoning and problem-solving.

Question 3

Generative AI

Answer 3

AI that creates original content, such as text, images, and audio, based on input data.

Question 4

Supervised Learning

Answer 4

A type of machine learning where models are trained using labeled data.

Question 5

Unsupervised Learning

Answer 5

A type of machine learning where models identify patterns without labeled data.

Question 6

Deep Learning

Answer 6

An advanced subset of machine learning using neural networks to mimic the human brain.

Question 7

Clustering

Answer 7

An unsupervised learning technique that groups data based on similarities.

Question 8

Regression

Answer 8

A supervised learning task that predicts continuous numerical values.

Question 9

Classification

Answer 9

A supervised learning task that predicts categorical outcomes.

Question 10

Natural Language Processing

Answer 10

AI that enables computers to understand, interpret, and respond to human language.

Question 11

Computer Vision

Answer 11

AI capabilities that enable systems to process and interpret visual data.

Question 12

Document Intelligence

Answer 12

AI for extracting, processing, and analyzing data from documents.

Question 13

Knowledge Mining

Answer 13

Extracting insights from large volumes of unstructured data to create searchable knowledge.

Question 14

Optical Character Recognition

Answer 14

A technique to detect and digitize text from images or scanned documents.

Question 15

Bounding Box

Answer 15

A rectangular region used in computer vision to identify object locations in images.

Question 16

Endpoint

Answer 16

The location or URL to access a resource, such as an Azure AI service.

Question 17

Key

Answer 17

A private string used to authenticate access to AI resources.

Question 18

REST API

Answer 18

An interface that allows applications to interact with services over HTTP.

Question 19

AutoML

Answer 19

Automated Machine Learning that simplifies model training and optimization tasks.

Question 20

Responsible AI

Answer 20

Principles ensuring ethical, fair, and safe development and deployment of AI systems.

Question 21

Azure AI Vision

Answer 21

Microsoft’s service for analyzing and processing visual data using AI.

Question 22

Azure AI Speech

Answer 22

Microsoft’s service for speech recognition, synthesis, and real-time translations.

Question 23

Azure AI Language

Answer 23

A service for building NLP solutions like text analysis and conversational AI.

Question 24

Fairness in AI

Answer 24

The principle that AI systems should treat all users and data without bias.

Question 25

Interpretability

Answer 25

The ability to understand and explain how AI systems make decisions.

Question 26

Reliability and Safety

Answer 26

Ensuring AI systems operate consistently and without causing harm.

Question 27

Transparency

Answer 27

Being open about AI systems’ purpose, functionality, and limitations.

Question 28

Inclusiveness

Answer 28

Designing AI systems that empower and engage diverse communities.

Question 29

Privacy and Security

Answer 29

Protecting data used in AI systems to ensure confidentiality and safety.

Question 30

MLOps

Answer 30

Practices for managing the deployment and lifecycle of machine learning models.