Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Data
contrastive learning
contrastive learning is a core generative-AI concept used across modeling, product, and governance discussions.
Data
ControlNet
ControlNet is a core generative-AI concept used across modeling, product, and governance discussions.
Training
cosine similarity
cosine similarity is a core generative-AI concept used across modeling, product, and governance discussions.
Data Processing
Data Annotation
The process of labeling data for training machine learning models.
Product
data contamination
data contamination is a core generative-AI concept used across modeling, product, and governance discussions.
Data Processing
data-augmentation
The process of increasing the size and diversity of a training dataset by applying transformations.
Data Processing
data-sourcing
The process of obtaining and collecting data from various sources.
Data Management
Dataset
A structured collection of data used for analysis and training machine learning models.
Data Management
Dataset Splitting
The process of dividing a dataset into training, validation, and test sets.
Safety
decoder-only
decoder-only is a core generative-AI concept used across modeling, product, and governance discussions.
Safety
diarization
diarization is a core generative-AI concept used across modeling, product, and governance discussions.
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.
Training
distillation
distillation is a core generative-AI concept used across modeling, product, and governance discussions.
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.
Data
encoder-decoder
encoder-decoder is a core generative-AI concept used across modeling, product, and governance discussions.
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.
Safety
eval harness
eval harness is a core generative-AI concept used across modeling, product, and governance discussions.
Ethics
Explainability
The ability to understand and interpret how AI models make decisions.
AI Ethics
Explainable AI
A branch of artificial intelligence focused on making the decision-making processes of models understandable to humans.