Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Machine Learning
Deep Learning
A subfield of machine learning that uses neural networks with many layers.
Media Technology
deepfake
A synthetic media in which a person in an image or video is replaced with someone else's likeness.
Safety
diarization
diarization is a core generative-AI concept used across modeling, product, and governance discussions.
privacy technology
differential-privacy
A method to ensure that individual data points cannot be identified in datasets.
Training
diffusion
diffusion is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
diffusion guidance
diffusion guidance is a core generative-AI concept used across modeling, product, and governance discussions.
Simulation
digital-twin
A virtual representation of a physical object or system used for simulation and analysis.
Data Processing
dimensionality-reduction
The process of reducing the number of features in a dataset while preserving important information.
Training
distillation
distillation is a core generative-AI concept used across modeling, product, and governance discussions.
Computing
Distributed Computing
A computing paradigm where processing is distributed across multiple machines or nodes.
Machine Learning
distributed-learning
A machine learning paradigm where the training data is distributed across multiple devices or nodes.
Machine Learning
domain-adaptation
A technique in machine learning that aims to improve model performance on a target domain by leveraging labeled data from a related source domain.
Data
DPO
DPO is a core generative-AI concept used across modeling, product, and governance discussions.
Regularization
Dropout
A regularization technique used to prevent overfitting in neural networks by randomly deactivating a fraction of neurons during training.
algorithm-design
dynamic-programming
A method for solving complex problems by breaking them down into simpler subproblems.
Computing
edge computing
Edge computing is a computing paradigm that brings computation and data storage closer to the location of the data source.
Product
embedding
An embedding maps text or media into a dense vector so similarity and retrieval can be computed geometrically.
Data
encoder-decoder
encoder-decoder is a core generative-AI concept used across modeling, product, and governance discussions.
Probabilistic Models
energy-based-model
A probabilistic model that associates a scalar energy value with each configuration of variables to model distributions.
Learning Techniques
Ensemble Learning
A technique that combines multiple models to improve overall performance.
Machine Learning
Ensemble Method
A technique that combines multiple models to improve performance.
Modeling Techniques
ensemble-methods
Techniques that combine multiple models to improve overall performance.
Inference
euclidean distance
euclidean distance is a core generative-AI concept used across modeling, product, and governance discussions.
Safety
eval card
eval card is a core generative-AI concept used across modeling, product, and governance discussions.