Big data analytics: The process of examining large and complex data sets (i.e., big data) to uncover hidden patterns, unknown correlations, and other useful insights, using advanced computing technologies and statistical algorithms.

Cognitive computing: A type of artificial intelligence that aims to simulate human thinking and reasoning, using techniques such as natural language processing, machine learning, and neural networks.

Explainable AI: A subfield of AI that aims to create models and systems that can provide transparent and interpretable explanations of their decision-making processes.

Fuzzy logic: A mathematical approach to reasoning that allows for uncertainty and ambiguity, using a system of logic that can handle imprecise or incomplete information.

Genetic algorithms: A type of optimization algorithm inspired by the process of natural selection, where solutions to a problem are represented as “chromosomes” and evolved over generations to find the best solution.

Human-in-the-loop: An approach to AI development that involves incorporating human feedback and oversight into the decision-making process, typically through human supervision or interaction.

Predictive modeling: A statistical technique that uses data mining and machine learning algorithms to build mathematical models that can predict future events or outcomes based on historical data.

Reinforcement learning: A type of machine learning that involves an agent learning to make decisions based on trial and error, with the goal of maximizing a reward signal.

Sentiment analysis: A natural language processing technique that uses machine learning algorithms to analyze and classify the emotional tone or sentiment expressed in text data (e.g., social media posts, product reviews, customer feedback, etc.).

Swarm intelligence: A collective behavior exhibited by decentralized, self-organized systems of agents (e.g., birds, bees, ants) that cooperate and interact with each other to solve complex problems or tasks, often using simple rules or behaviors. In artificial intelligence, swarm intelligence algorithms are used to solve optimization and decision-making problems.

Transfer learning: A machine learning technique that involves leveraging knowledge gained from one task or domain to improve performance on a different but related task or domain.

Unsupervised learning: A type of machine learning that involves discovering patterns and relationships in data without explicit guidance or supervision.