Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Data
self-consistency
self-consistency is a core generative-AI concept used across modeling, product, and governance discussions.
Neural Networks
Self-Organizing Map
A type of neural network used for unsupervised learning that maps high-dimensional data to lower dimensions.
Machine Learning
Self-supervised Learning
A type of machine learning where the model learns from unlabeled data by generating its own labels.
Data
semantic search
Semantic search retrieves by meaning (often via embeddings), not only keyword overlap.
Computer Vision
Semantic Segmentation
The task of classifying each pixel in an image into a category.
Web Technologies
semantic web
The semantic web is an extension of the World Wide Web that enables data to be shared and reused across applications.
Machine Learning
semi-supervised-learning
A learning approach that combines labeled and unlabeled data for training models.
Natural Language Processing
sentiment-analysis
The use of natural language processing to determine the emotional tone behind words.
Optimization Techniques
Simulated Annealing
A probabilistic technique for approximating the global optimum of a given function.
modeling
simulation
The imitation of the operation of a real-world process or system over time.
Blockchain
Smart Contracts
Self-executing contracts with the terms of the agreement directly written into code.
data analysis
social-network-analysis
The study of social relationships and structures through networks and graph theory.
Product
softmax
Softmax converts a vector of logits into a probability distribution over classes or tokens.
machine-learning
sparce-activation
A technique in neural networks that activates only a small subset of neurons for each input.
Product
sparse activation
sparse activation is a core generative-AI concept used across modeling, product, and governance discussions.
Data Representation
sparse-coding
A representation method that encodes data with a small number of active features.
Signal Processing
sparse-representation
A method in signal processing where signals are represented with a small number of non-zero coefficients.
data-analysis
spatial-temporal-analysis
The study of data that varies across both space and time to uncover patterns and trends.
Data
speech-to-text
speech-to-text is a core generative-AI concept used across modeling, product, and governance discussions.
Data Sampling
stratified-sampling
A sampling method that ensures representation from different subgroups in a dataset.
Safety
structured output
structured output is a core generative-AI concept used across modeling, product, and governance discussions.
Machine Learning
Supervised Learning
A type of machine learning where the model learns from labeled data.
Machine Learning
Support Vector Machine (SVM)
A supervised learning model used for classification and regression tasks.
Machine Learning
support-vector-machine
A supervised learning algorithm used for classification and regression tasks.