AI Vocabulary and Studying
Important AI vocabulary to help students talk about AI and understand common terms used by people discussing AI.
A field of computer science that focuses on creating machines capable of intelligent behavior. A subset of AI that involves the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world. A series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. A branch of AI that helps computers understand, interpret and manipulate human language. A software application used to conduct an on-line chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human agent. A set of rules or procedures for solving a problem or accomplishing a task, often used in the context of computer programming and AI. A subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. The process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. A test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. A type of machine learning where the AI system is provided with labeled training data and the desired outputs. A type of machine learning where the AI system is provided with unlabeled training data and must find patterns and relationships within the data. A type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a goal. A field of engineering focused on the design and manufacturing of robots, often incorporating elements of AI. A field of AI that trains computers to interpret and understand the visual world. The consideration of how AI systems should make decisions, and the impact of AI on society, including issues like privacy, bias, and job displacement.1. Artificial Intelligence (AI)
2. Machine Learning
3. Neural Network
4. Natural Language Processing (NLP)
5. Chatbot
6. Algorithm
7. Deep Learning
8. Data Mining
9. Turing Test
10. Supervised Learning
11. Unsupervised Learning
12. Reinforcement Learning
13. Robotics
14. Computer Vision
15. Ethics in AI