Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
machine-learning
model-interpretation
The process of understanding and explaining the predictions made by a machine learning model.
modeling
model-trained
The process of training a machine learning model using data.
Safety
MT-Bench
MT-Bench is a core generative-AI concept used across modeling, product, and governance discussions.
Training
multi-head attention
multi-head attention is a core generative-AI concept used across modeling, product, and governance discussions.
Artificial Intelligence
Natural Language Processing (NLP)
The field of AI that focuses on the interaction between computers and human language.
Machine Learning
Neural Network
A computational model inspired by the way biological neural networks in the human brain work.
Inference
noise scheduler
noise scheduler is a core generative-AI concept used across modeling, product, and governance discussions.
information-theory
noisy-channel-coding
A method for encoding data to protect against errors during transmission over noisy channels.
data-quality
noisy-labels
Labels in a dataset that are inaccurate or wrong, often leading to misguidance in model training.
machine learning
one-shot-learning
A machine learning approach that enables a model to learn information about object categories from a single training example.
Knowledge Representation
ontologies
Formal representations of a set of concepts within a domain and the relationships between those concepts.
Knowledge Representation
ontology
An ontology is a formal representation of a set of concepts within a domain.
Data
open weights
open weights is a core generative-AI concept used across modeling, product, and governance discussions.
machine learning
out-of-distribution-generalization
The ability of a model to perform well on unseen data that is different from the training set.
Modeling
Overfitting
A modeling error that occurs when a model learns noise and details from the training data.
Product
pgvector
pgvector is a core generative-AI concept used across modeling, product, and governance discussions.
Training
PII detection
PII detection is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
positional encoding
positional encoding is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
PPO
PPO is a core generative-AI concept used across modeling, product, and governance discussions.
Safety
preference optimization
preference optimization is a core generative-AI concept used across modeling, product, and governance discussions.
Data
privacy redaction
privacy redaction is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
QLoRA
QLoRA is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
quantization
quantization is a core generative-AI concept used across modeling, product, and governance discussions.
Quantum Physics
quantum-entanglement
A physical phenomenon occurring when pairs or groups of particles interact in such a way that the quantum state of each particle cannot be described independently.