Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Machine Learning
support-vector-regression
An extension of support vector machines that predicts continuous values instead of categories.
Artificial Intelligence
swarm intelligence
Swarm intelligence is the collective behavior of decentralized systems typically seen in nature.
Data Science
synthetic-data-generation
The process of creating artificial data that mimics real-world data for training machine learning models.
NLP
task-oriented-dialogue-systems
Systems designed to manage specific tasks through natural language conversation.
Safety
temperature
Temperature scales randomness in sampling: lower values are more deterministic; higher values explore more.
Deep Learning
temporal-convolutional-network
A type of neural network designed for sequence modeling using convolutional layers.
Data Analysis
Time Series Analysis
A method used to analyze time-ordered data points to extract meaningful statistics and characteristics.
Data Analysis
Time Series Forecasting
The process of predicting future values based on previously observed values in a time-ordered series.
Training
token
A token is the smallest unit a model consumes or generates; pricing and context limits are expressed in tokens.
Natural Language Processing
Tokenization
The process of converting text into smaller pieces, called tokens.
Agents
Tool calling
Tool calling lets a model request that the application run a defined function, API, or built-in tool, then return the result to the model.
Training
top-k
Top-k sampling restricts each step to the k highest-probability tokens.
Data
top-p
Top-p (nucleus) sampling keeps the smallest set of tokens whose cumulative probability exceeds p.
Control Systems
Transfer Function
A mathematical representation of the relationship between input and output of a system.
Learning Techniques
Transfer Learning
A machine learning technique where a model developed for one task is reused for a different but related task.
Product
transformer
A transformer is an architecture built from attention layers; most frontier LLMs are decoder-only or encoder–decoder transformers.
Deep Learning
transformer-architecture
A neural network architecture designed for sequence-to-sequence tasks.
Machine Learning
Unsupervised Learning
A type of machine learning that deals with data that has no labels, aiming to find hidden patterns or intrinsic structures.
Reinforcement Learning
unsupervised-reinforcement-learning
A learning paradigm where agents learn optimal behaviors through exploration without labeled feedback.
Model Evaluation
Variance
Variance measures a model's sensitivity to fluctuations in the training data, contributing to overfitting when high.
Generative Models
variational-autoencoder
A generative model that learns to represent data in a latent space using variational inference.
Safety
vector
A vector is a fixed-length array of numbers; embeddings represent meaning as vectors for search and clustering.
Data
Vector database
A database or engine optimized for similarity search over embedding vectors, typically with metadata filters and hybrid lexical+vector queries for production RAG.
Retrieval
Vector search
Vector search retrieves semantically similar items by comparing embedding vectors rather than relying only on exact keyword overlap.