artificial intelligence dictionary

Artificial general intelligence (AGI): The hypothetical development of an AI that is capable of learning any intellectual task that a human can.
Artificial intelligence (AI): The simulation of human intelligence processes by computer systems, including tasks such as learning, reasoning, and self-correction.
Automated reasoning: The use of computer programs to generate logical conclusions and solve problems.
Autonomous vehicles: Self-driving cars or other vehicles that can operate without human intervention.
Backpropagation: An algorithm used to train artificial neural networks in deep learning.
Big data: Extremely large data sets that can be analyzed computationally to reveal patterns, trends, and associations.
Chatbots: Computer programs designed to simulate conversation with human users, often used for customer service or support.
Cognitive computing: The simulation of human thought processes in a computerized model, including natural language processing and pattern recognition.
Computer vision: The ability of computers to interpret and analyze visual data from the world around them, often used for image recognition.
Data mining: The process of discovering patterns and relationships in large data sets through analysis and machine learning techniques.
Decision trees: A predictive modeling tool that uses a tree-like graph to map out all possible outcomes and their probabilities.
Deep learning: A subset of machine learning that involves neural networks with many layers, allowing for more complex data analysis and pattern recognition.
Expert systems: Computer programs that use a knowledge base and decision-making algorithms to solve problems or provide advice in a specific domain.
Genetic algorithms: Optimization algorithms that use principles of natural selection and genetics to find the best solutions to complex problems.
Image recognition: The ability of computers to identify and classify objects in images and video streams.
Intelligent agents: Computer programs that can perform specific tasks on behalf of users, often using machine learning or other AI techniques.
Machine learning: The process by which a computer system can learn from data and improve its performance on a specific task over time.
Natural language processing (NLP): The ability of computers to understand, interpret, and generate human language, often used for voice assistants and chatbots.
Neural networks: A set of algorithms modeled after the human brain that can learn and improve their performance on tasks through training on data.
Predictive analytics: The use of statistical and machine learning algorithms to predict future outcomes based on historical data.
Reinforcement learning: A machine learning technique in which an agent learns to take actions in an environment in order to maximize a reward signal.
Robotics: The design, construction, and operation of robots, often using AI techniques to enable them to perform complex tasks.
Speech recognition: The ability of computers to convert spoken language into text or other digital formats.
Supervised learning: A type of machine learning in which the computer is given labeled data to learn from, allowing it to make predictions about new data.
Unsupervised learning: A type of machine learning in which the computer is given unlabeled data and must find patterns or structure on its own.
Virtual assistants: AI-powered software applications that can perform a variety of tasks on behalf of users, often using natural language processing and machine learning techniques.
Weak AI: AI that is designed for a specific task or set of tasks, as opposed to strong AI, which is intended to be capable of any intellectual task that a human can do.