Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
computer-vision
image-segmentation
The process of partitioning an image into multiple segments to simplify analysis.
Machine Learning
incremental-learning
A machine learning approach that updates models continuously with new data without retraining from scratch.
Models
Indic LLM
An Indic LLM is a language model optimized for Indian languages, scripts, romanized text, code-mixing, and India-specific cultural or domain context.
Agent security
Indirect prompt injection
Indirect prompt injection happens when untrusted external content, such as a webpage, email, document, or tool result, contains instructions that try to steer an AI system.
Data Management
information-retrieval
The process of obtaining information system resources that are relevant to an information need.
Networking
internet-of-things-iot
A network of interconnected devices that communicate and exchange data over the internet.
Unsupervised Learning
k-means-clustering
An unsupervised learning algorithm used for partitioning data into clusters.
Machine Learning
K-Nearest Neighbors (KNN)
A simple algorithm that classifies data points based on the classes of their nearest neighbors.
Model Optimization
Knowledge Distillation
A process of transferring knowledge from a large model to a smaller model.
Data Representation
Knowledge Graph
A structured representation of knowledge that connects entities and their relationships, typically used in AI for information retrieval.
AI Foundations
Knowledge Representation
The method of encoding information about the world into a format that a computer system can utilize.
Knowledge Representation
knowledge-base
A repository of structured information and facts for inferencing and decision-making.
Data Preparation
Labeling
The process of assigning a specific tag or category to data.
Models
Large language model
A large language model, or LLM, is a neural text model trained on large corpora to predict, generate, transform, and reason over language and code.
Statistical Models
Latent Variable Model
A statistical model that assumes the existence of unobserved variables that influence observed data.
Model Training
Learning Rate
The learning rate is a hyperparameter that controls how much to change the model weights in response to the estimated error each time the model weights are updated.
Evaluation
LLM evaluation
LLM evaluation measures whether a model or AI workflow is accurate, useful, safe, reliable, and cost-effective for a target task.
Inference
logit
A logit is an unnormalized score for a vocabulary item before softmax turns it into a probability.
Model Capabilities
Long Context
Long context is an LLM's ability to accept a large token window containing prompts, documents, conversation history, tool results, and generated output.
Evaluation Metrics
Loss Function
A method of evaluating how well a specific algorithm models the given data.
Machine Learning
Machine Learning
A subset of AI that enables systems to learn from data and improve over time.
Agents
MCP server
An MCP server exposes tools, data sources, prompts, or workflows to AI clients through the Model Context Protocol.
Optimization
meta-heuristics
A class of optimization algorithms that use iterative processes to find solutions.
Machine Learning
Meta-Learning
Learning to learn, where models improve their learning strategies over time.