Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Neural Networks
Activation Function
A mathematical function that determines the output of a neural network layer.
Machine Learning
Active Learning
A machine learning paradigm where the model can query a user to obtain labels for new data points actively.
signal-processing
adaptive-filtering
A technique for dynamically adjusting filter parameters based on input signal characteristics.
Machine Learning
adaptive-learning
A method where the system optimizes its learning process based on user interactions and performance.
Security
adversarial-example
An input designed to fool a machine learning model into making incorrect predictions.
Machine Learning
adversarial-training
A method of training models to be robust against adversarial examples.
General Concepts
Algorithm
A step-by-step procedure for calculations or problem-solving.
Data
alignment
alignment is a core generative-AI concept used across modeling, product, and governance discussions.
Data Analysis
anomaly
An anomaly is a data point that deviates significantly from the expected pattern.
machine-learning
anomaly-detection
A technique used to identify unusual patterns or outliers in data.
Data
arena
arena is a core generative-AI concept used across modeling, product, and governance discussions.
Deep Learning
Artificial Neural Network (ANN)
A computational model inspired by the way biological neural networks function.
Data
assistant message
assistant message is a core generative-AI concept used across modeling, product, and governance discussions.
Safety
attention
Attention weights how much each token should attend to others when producing representations.
Neural Networks
Attention Mechanism
A technique that allows models to focus on specific parts of the input data when making predictions.
Data Augmentation
augment-data
A technique to artificially increase the size of a training dataset by creating modified copies of existing data.
Data Preparation
Augmented Data
Synthetic data created to enhance the diversity and quantity of training datasets.
Interactive Technology
Augmented Reality
An interactive experience that overlays digital information onto the real world.
deep learning
auto-encoding
A type of artificial neural network used to learn efficient codings of unlabeled data.
neural networks
autoencoder
An autoencoder is a type of neural network used for unsupervised learning of efficient representations.
Machine Learning
Automated Machine Learning (AutoML)
A process that automates the end-to-end process of applying machine learning to real-world problems.
Data Science
automated-data-analysis
The use of algorithms and software to analyze data without human intervention.
Machine Learning
AutoML
Automated Machine Learning streamlines the process of applying machine learning to real-world problems.
AI Concepts
Autonomous Agents
Systems that can operate independently to perform tasks without human intervention.