AI Terminology
Welcome to the AI Terminology section of the AI blog! This comprehensive glossary is designed to help you navigate the complex world of artificial intelligence. Here, you’ll find clear, concise definitions and explanations of key terms and concepts in AI, from foundational ideas like machine learning and neural networks to advanced topics such as reinforcement learning and variational autoencoders. Whether you’re a beginner or an expert, this resource is tailored to enhance your understanding and keep you updated with the latest advancements in the field.
Variational Autoencoder (VAE)
A Variational Autoencoder (VAE) is a type of artificial neural network used in the field of machine learning for the purpose of generating new data.
Recurrent Neural Network (RNN)
A recurrent neural network (RNN) is a type of neural network that is designed to handle sequences of data.
Machine Learning (ML)
Machine learning is a subset of artificial intelligence (AI) that enables computers to learn from experience and improve over time.
Supervised Learning
Supervised learning is a type of machine learning algorithm that involves learning from a set of training data that has been labeled with the correct answers.
Reinforcement Learning • RL
Reinforcement learning is a subfield of machine learning, concerned with how software agents can learn to behave in complex, uncertain environments. It relies on feedback from the environment in order to improve the agent's behavior.
Human-Computer Interface • HCI
A human-computer interface is the point of contact between a human user and a computer system.
Abstraction
Abstraction is a widely used concept in artificial intelligence to manage the use of different levels of detail in a representation language or the ability to switch between levels while preserving important characteristics.
Note: The above list of AI terms is sorted by the last update time.
AI Terminology Graph (interactive)
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