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Glossary

Terms and definitions.

Term Definition Last Updated
Activation Function A mathematical function applied to the output of a neuron in a neural network that determines whe... 2025-08-31
AI Agents Autonomous artificial intelligence systems designed to perceive their environment, make decisions... 2025-09-10
AI Alignment The challenge of ensuring AI systems act in accordance with human values and intentions. As AI be... 2025-08-31
Algorithm A set of rules or instructions designed to solve a specific problem or perform a computation. In ... 2025-08-31
Artificial Intelligence The simulation of human intelligence in machines that are programmed to think and learn like huma... 2025-08-31
Artificial Neural Network A computational model inspired by biological neural networks, consisting of interconnected nodes ... 2025-08-31
Attention Mechanism A technique that allows neural networks to focus on specific parts of the input when producing ou... 2025-08-31
Autoencoder A type of neural network trained to copy its input to its output through a bottleneck layer. Auto... 2025-08-31
Autoregressive A type of model that predicts future values based on previous values in a sequence. In language m... 2025-08-31
Backpropagation A supervised learning algorithm used to train neural networks by calculating gradients of the los... 2025-08-31
Batch Normalization A technique used in deep neural networks to normalize inputs to each layer, reducing internal cov... 2025-08-31
BERT Bidirectional Encoder Representations from Transformers, a pre-trained transformer model that lea... 2025-08-31
Bias-Variance Tradeoff A fundamental concept in machine learning describing the tradeoff between bias (error from oversi... 2025-08-31
Chain-of-Thought Prompting A prompting technique that encourages language models to generate step-by-step reasoning processe... 2025-09-10
Classification A supervised learning task where the goal is to predict discrete categorical labels or classes fo... 2025-08-31
Clustering An unsupervised learning technique that groups similar data points together into clusters. The go... 2025-08-31
Computer Vision A field of artificial intelligence that enables machines to interpret and analyze visual informat... 2025-08-31
Constitutional AI A training approach developed by Anthropic that aims to create AI systems guided by a set of prin... 2025-09-10
Convolutional Neural Network A deep learning architecture designed to process grid-like data such as images. CNNs use convolut... 2025-08-31
Cross-Validation A resampling technique used to assess how well a machine learning model will generalize to indepe... 2025-08-31
Deep Learning A subset of machine learning that uses artificial neural networks with multiple layers to model a... 2025-08-31
Dimensionality Reduction The process of reducing the number of features or variables in a dataset while preserving importa... 2025-08-31
Dropout A regularization technique used in neural networks to prevent overfitting by randomly setting a f... 2025-08-31
Feature An individual measurable property or characteristic of an object being observed. In machine learn... 2025-08-31
Feature Engineering The process of selecting, modifying, or creating features from raw data to improve machine learni... 2025-08-31
Few-Shot Learning A machine learning approach where models learn to perform tasks with only a few examples. In the ... 2025-08-31
Fine-tuning The process of adapting a pre-trained model to a specific task or domain by continuing training o... 2025-08-31
Foundation Models Large-scale AI models trained on broad, diverse datasets that serve as a foundation for a wide ra... 2025-09-10
Gated Recurrent Unit A simplified variant of LSTM that uses gating mechanisms to control information flow in recurrent... 2025-08-31
Generalization The ability of a machine learning model to perform well on new, unseen data that was not part of ... 2025-08-31
Generative Adversarial Network A deep learning architecture consisting of two neural networks competing against each other: a ge... 2025-08-31
GPT Generative Pre-trained Transformer, a family of autoregressive language models that generate text... 2025-08-31
Gradient Descent An optimization algorithm used to minimize loss functions by iteratively moving in the direction ... 2025-08-31
Image Classification A computer vision task where algorithms assign category labels to entire images. The goal is to d... 2025-08-31
In-Context Learning The ability of language models to learn and adapt to new tasks during inference by using examples... 2025-08-31
Inference The process of using a trained machine learning model to make predictions or decisions on new, un... 2025-08-31
Large Language Model A type of artificial intelligence model that has been trained on vast amounts of text data to und... 2024-08-28
Long Short-Term Memory A type of recurrent neural network architecture that can learn long-term dependencies in sequenti... 2025-08-31
Machine Learning A subset of artificial intelligence that enables computers to learn and improve from experience w... 2025-08-31
Masked Language Model A training objective where random tokens in a sequence are masked (hidden) and the model learns t... 2025-08-31
Mixture of Experts (MoE) A neural network architecture that uses multiple specialized sub-networks (experts) along with a ... 2025-09-10
Model A mathematical representation of a real-world process, created by training an algorithm on data. ... 2025-08-31
Multi-Head Attention An extension of self-attention that runs multiple attention mechanisms in parallel, each focusing... 2025-08-31
Multilayer Perceptron A feedforward artificial neural network with multiple layers of nodes between input and output la... 2025-08-31
Multimodal Models AI models capable of processing, understanding, and generating content across multiple modalities... 2025-09-10
Natural Language Processing A branch of artificial intelligence that focuses on the interaction between computers and human l... 2025-08-31
Neural Network A computing system inspired by biological neural networks. It consists of interconnected nodes (n... 2025-08-31
Object Detection A computer vision task that involves identifying and localizing objects within images or videos. ... 2025-08-31
Overfitting A modeling error that occurs when a machine learning model learns the training data too well, inc... 2025-08-31
Perceptron A single-layer neural network that is the simplest type of artificial neural network. It consists... 2025-08-31
Pre-training The initial training phase where a model learns general patterns from large amounts of unlabeled ... 2025-08-31
Prompt Input text or instructions given to a language model to guide its output generation. Effective pr... 2025-08-31
Prompt Engineering The practice of designing and optimizing prompts to effectively communicate with language models ... 2025-08-31
Recurrent Neural Network A type of neural network designed to process sequential data by maintaining internal memory throu... 2025-08-31
Regression A supervised learning task where the goal is to predict continuous numerical values for given inp... 2025-08-31
Reinforcement Learning A type of machine learning where an agent learns to make decisions by taking actions in an enviro... 2025-08-31
Reinforcement Learning from Human Feedback (RLHF) A training methodology that uses human preferences to fine-tune language models and other AI syst... 2025-09-10
ReLU Rectified Linear Unit, an activation function that outputs the input directly if positive, otherw... 2025-08-31
Retrieval-Augmented Generation (RAG) A framework that enhances language models by combining parametric knowledge stored in model weigh... 2025-09-10
Self-Attention An attention mechanism where each element in a sequence attends to all elements in the same seque... 2025-08-31
Semantic Segmentation A computer vision task that assigns a class label to every pixel in an image, creating pixel-leve... 2025-08-31
Supervised Learning A type of machine learning where algorithms learn from labeled training data to make predictions ... 2025-08-31
Test-Time Compute A scaling paradigm that improves AI model performance by allocating additional computational reso... 2025-09-10
Tokenization The process of breaking down text into smaller units called tokens, such as words, subwords, or c... 2025-08-31
Tool Use (Function Calling) The ability of AI models, particularly language models, to interact with external tools, APIs, an... 2025-09-10
Training Data The dataset used to teach a machine learning algorithm. It consists of input examples and their c... 2025-08-31
Transformer A neural network architecture that relies entirely on attention mechanisms to process sequential ... 2025-08-31
Underfitting A modeling error that occurs when a machine learning model is too simple to capture the underlyin... 2025-08-31
Unsupervised Learning A type of machine learning that finds patterns in data without labeled examples. The algorithm di... 2025-08-31
Variational Autoencoder A type of autoencoder that learns a probabilistic latent representation of data. VAEs can generat... 2025-08-31
Zero-Shot Learning A learning paradigm where models perform tasks without having seen specific examples during train... 2025-08-31

71 terms