Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Neural Networks
Generative Adversarial Network (GAN)
A generative adversarial network (GAN) trains a generator and a discriminator in opposition so the generator learns to produce samples that resemble a training distribution.
Artificial Intelligence
Generative AI
AI systems that can create new content, such as text, images, or music.
Modeling
Generative Model
A generative model learns a data distribution so it can create new samples such as text, images, audio, code, or structured records.
Evaluation
Golden set
A golden set is a versioned collection of labeled tasks used to score models and prompts against the behavior you actually want.
Machine Learning
Gradient Boosting
A machine learning technique that builds models in a sequential manner.
Optimization
Gradient Descent
An optimization algorithm used to minimize the loss function in machine learning.
Machine learning
Graph Machine Learning
Graph machine learning applies statistical and neural methods to data represented as nodes, edges, and attributes so models can learn from relationships as well as individual records.
Machine Learning
graph-attention-network
A neural network architecture that employs attention mechanisms to process graph-structured data.
Neural Networks
graph-convolutional-network
A type of neural network designed to process data structured as graphs.
Database Technology
graph-database
A database specifically designed to store and navigate relationships between data points using graph structures.
machine-learning
graph-embedding
A technique for transforming graph-structured data into a continuous vector space while preserving its properties.
Deep Learning
graph-neural-network
A neural network designed to work directly with graph-structured data.
Mathematics
graph-theory
A field of mathematics focused on the study of graphs as mathematical structures.
Statistics
graphical-models
Statistical models that represent variables and their conditional dependencies using a graph.
Model Training
grid-search
A method for hyperparameter optimization that exhaustively searches through a specified subset of hyperparameters.
Retrieval
Grounding
Grounding means tying model claims to retrieved documents, tools, or other checkable evidence instead of parametric memory alone.