AI Glossary

1. Artificial Intelligence (AI)
The simulation of human intelligence processes by computer systems. These processes include learning, reasoning, and self-correction.

2. Machine Learning (ML)
A subset of AI that involves the use of algorithms and statistical models to enable computers to improve their performance on a task through experience.

3. Deep Learning
A subset of machine learning that uses neural networks with many layers (deep neural networks) to analyze various factors of data.

4. Neural Network
A series of algorithms that attempt to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.

5. Natural Language Processing (NLP)
A field of AI that gives machines the ability to read, understand, and derive meaning from human languages.

6. Computer Vision
An AI field that trains computers to interpret and make decisions based on visual data from the world.

7. Reinforcement Learning
A type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve maximum cumulative reward.

8. Supervised Learning
A type of machine learning where the model is trained on labeled data, meaning the input comes with the correct output.

9. Unsupervised Learning
A type of machine learning where the model is trained on unlabeled data and must find patterns and relationships in the data on its own.

10. Algorithm
A set of rules or instructions given to an AI system to help it learn on its own.

11. Big Data
Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

12. Data Mining
The process of discovering patterns and knowledge from large amounts of data.

13. Predictive Analytics
The use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.

14. Autonomous Agents
Software entities that carry out tasks on behalf of users with some degree of independence or autonomy, and in so doing, employ some knowledge or representation of the user’s goals or desires.

15. AI Ethics
The branch of ethics that examines the moral implications and societal impact of AI technologies.