Artificial intelligence refers to the development of computer systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and natural language understanding.
Generative artificial intelligence refers to algorithms and models that can generate new content or data, such as images, videos, music, or text, based on patterns learned from existing information.
Machine learning is a subset of artificial intelligence that involves training computer systems to learn from data and improve their performance over time through experience.
NLP is a subfield of artificial intelligence that deals with the interactions between computers and human language, including text and speech processing, sentiment analysis, machine translation, and dialogue systems.
A chatbot is a software application that uses natural language processing (NLP) and machine learning (ML) to simulate conversation with humans, either via text or voice interfaces.
A large language model is a type of machine learning model that is trained on vast amounts of text data to generate language outputs that are coherent and contextually appropriate.
Prompt engineering is the process of designing and refining prompts to elicit desired responses or behaviors from AI systems, in order to improve their performance and versatility.
In the context of AI, hallucination refers to the phenomenon where a model generates inaccurate or imaginary output that cannot be explained by its training data.
Definitions provided by University of Texas Libraries' Artificial Intelligence LibGuide under a Creative Commons Attribution-NonCommercial 4.0 Generic License.