Machine Learning

A/B Testing

A/B testing (also called split testing, bucket testing, or an online controlled experiment) is a randomized controlled experiment that compares two variants, a...

Data ScienceStatistics

AI Alignment

AI alignment is the field of AI research dedicated to ensuring that artificial intelligence systems pursue the goals, values, and intentions their human...

AI EthicsAI Safety

AI Drug Discovery

AI drug discovery refers to the use of artificial intelligence techniques, including machine learning, deep learning, generative models, and natural language...

AI Tools & ProductsArtificial Intelligence

AI agents

This article covers contemporary LLM-based AI agents in practice: their architectures, frameworks, protocols, products, benchmarks, enterprise adoption, and...

AI AgentsArtificial Intelligence

AI for Science

AI for science is the use of artificial intelligence, particularly deep learning and large language models, to accelerate scientific discovery across biology,...

Artificial Intelligence

AQLM (Additive Quantization of Language Models)

AQLM, short for Additive Quantization of Language Models, is a weight-only post-training quantization method that compresses the weights of a large language...

AI Infrastructure

ARC-AGI-2

ARC-AGI-2 (Abstraction and Reasoning Corpus for Artificial General Intelligence 2) is an abstract reasoning benchmark for artificial intelligence, released on...

2025 in artificial intelligenceAI Benchmarks

ARIMA

ARIMA (Autoregressive Integrated Moving Average) is a class of statistical models for analyzing and forecasting time series data, specified by three...

Statistics

AUC (Area Under the ROC Curve)

AUC (Area Under the ROC Curve) is a classifier evaluation metric equal to the probability that a model ranks a randomly chosen positive instance higher than a...

Model Evaluation

AUC-ROC

See also: Machine learning terms AUC (Area Under the Curve), most often the area under the ROC curve (AUC-ROC), is a threshold-independent evaluation metric...

Model EvaluationStatistics

Abacus.AI

Abacus.AI is an American enterprise artificial intelligence and machine learning platform company headquartered in San Francisco, California. The firm was...

AI CompaniesDeveloper Tools

Absolute Zero Reasoner

Absolute Zero is a reinforcement learning paradigm for training reasoning models in which a single model proposes its own tasks and then solves them, using...

Deep Learning

Accuracy

See also: machine learning terms, confusion matrix, precision, recall, F1 score Accuracy is a classification metric that measures the fraction of predictions a...

Model Evaluation

Action (Reinforcement Learning)

In reinforcement learning (RL), an action is a decision or move made by an agent that affects the state of the environment. At each discrete time step, the...

Reinforcement Learning

Action Chunking with Transformers (ACT)

Action Chunking with Transformers (ACT) is an imitation learning algorithm for fine-grained robotic manipulation that predicts a short sequence (a "chunk") of...

RoboticsTransformer Models

Activation Function

An activation function is a nonlinear mathematical function applied to the output of each neuron in an artificial neural network, and it is what gives the...

Deep LearningNeural Networks

Active Learning

Active learning is a subfield of machine learning in which the learning algorithm interactively chooses which data points it wants labeled, querying an oracle...

AdaBoost

AdaBoost (short for Adaptive Boosting) is a machine learning ensemble algorithm that combines many weak classifiers into a single strong classifier through a...

AdamW

AdamW is a variant of the Adam optimizer that decouples weight decay from the gradient-based update rule, applying the decay directly to the weights instead of...

Training & Optimization

Agentic Context Engineering

Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve...

AI AgentsArtificial Intelligence

Agglomerative clustering

Agglomerative clustering is a bottom-up form of hierarchical clustering used in unsupervised learning in which each data point starts in its own singleton...

AlexNet

AlexNet is a deep learning convolutional neural network, built by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton at the University of Toronto, that won...

Computer VisionDeep Learning

Algorithmic fairness

Algorithmic fairness is the study of how automated decision systems can be made to produce decisions that are equitable across protected attributes such as...

AI EthicsAI Safety

AlphaFold

AlphaFold is an artificial intelligence system developed by Google DeepMind that predicts the three-dimensional structure of a protein directly from its amino...

Artificial IntelligenceGoogle

Amazon SageMaker

Amazon SageMaker is Amazon Web Services' fully managed machine learning platform for building, training, and deploying models at scale, first launched at AWS...

AI InfrastructureAI Tools & Products

Andrew Barto

Andrew Barto is an American computer scientist and one of the founders of modern reinforcement learning, the branch of machine learning in which an agent...

PeopleReinforcement Learning

Andrew Ng

Andrew Ng is a British-American computer scientist and entrepreneur who is one of the most influential figures in modern artificial intelligence, best known...

Artificial Intelligence

Anomaly Detection

In machine learning, anomaly detection is the process of identifying data points, events, or observations that deviate significantly from normal patterns in a...

Data Science

Area under the PR curve

See also: Machine learning terms The area under the precision-recall curve (AUPRC), also known as average precision (AP) or PR-AUC, is a scalar summary of a...

Area under the curve

Area under the curve (AUC) is a single scalar metric that summarizes the performance of a binary classifier or diagnostic test across all possible decision...

Model EvaluationStatistics

Artificial Intelligence

Artificial intelligence (AI) is the field of computer science dedicated to creating systems that perform tasks normally requiring human intelligence, such as...

Artificial IntelligenceComputer Science

Attention

See also: Machine learning terms > This article gives a high-level overview of attention as a family of mechanisms in machine learning. For deeper treatments,...

Deep LearningNeural Networks

Attention Is All You Need

"Attention Is All You Need" is the 2017 research paper that introduced the transformer, the neural network architecture that underpins virtually every modern...

Deep LearningNatural Language Processing

Attribute

In machine learning and data mining, an attribute is an individual measurable property of an object, observation, or example that describes the instance being...

Attribute sampling

See also: Machine learning terms Attribute sampling is a randomization technique in which a decision tree considers only a small, randomly drawn subset of the...

Audio Classification Models

Audio classification models are machine learning systems for audio classification, the task of assigning one or more labels to an audio recording or to short...

Deep LearningSpeech & Audio AI

Automatic Differentiation

Automatic differentiation (abbreviated AD, also called algorithmic differentiation, autodiff, or autograd) is a family of techniques for computing exact...

AI InfrastructureMathematics

Automation Bias

Automation bias is the tendency for humans to favor suggestions and outputs from automated decision-making systems over contradictory information from...

AI Ethics

Autoregressive Model

An autoregressive model predicts each element of a sequence from the elements that precede it, feeding its own earlier outputs back in as context for every...

Large Language Models

Average Precision

See also: precision, recall, F1 score, confusion matrix, AUC, precision-recall curve Average precision (AP) is an evaluation metric that summarizes the...

Computer VisionInformation Retrieval

Axis-aligned condition

In a decision tree, an axis-aligned condition is a split test at an internal node that involves only a single feature, comparing that one feature against a...

BERTScore

BERTScore is an automatic, reference-based metric for evaluating text generation that scores a candidate sentence against one or more references by comparing...

Model EvaluationNatural Language Processing

BIG-Bench

BIG-Bench (Beyond the Imitation Game Benchmark) is a large-scale, collaborative benchmark of 204 tasks, contributed by 450 authors across 132 institutions,...

AI BenchmarksLarge Language Models

BIG-Bench Hard

BIG-Bench Hard (BBH) is a suite of 23 challenging tasks drawn from the BIG-Bench benchmark, selected because they are "the [tasks] for which prior language...

AI BenchmarksNatural Language Processing

BLEU (Bilingual Evaluation Understudy)

BLEU (Bilingual Evaluation Understudy) is an automatic evaluation metric that scores the quality of machine translation output by measuring how many word...

Model EvaluationNatural Language Processing

Backpropagation

Backpropagation (short for "backward propagation of errors") is the algorithm used to compute the gradient of a scalar loss function with respect to every...

Deep LearningNeural Networks

Bag of Words

The bag of words (BoW) model is a text representation method that converts a document into a fixed-length numeric vector by counting how often each word from a...

Natural Language Processing

Bagging

See also: Machine learning terms, Ensemble methods, Random forest, Boosting Bagging, short for bootstrap aggregating, is an ensemble learning technique in...

Baseline

In machine learning, a baseline is a simple reference model or method used as a point of comparison to judge whether a more complex model actually adds value....

Model Evaluation

Batch

See also: machine learning terms, batch size, gradient descent A batch in machine learning is the set of training examples processed together in one forward...

Deep Learning

Batch Normalization

See also: Machine learning terms Batch normalization (often abbreviated BatchNorm or BN) is a technique for improving the speed, stability, and performance of...

Deep LearningNeural Networks

Batch Size

In machine learning, batch size is the hyperparameter that sets how many training examples a model processes together before it updates its parameters with one...

Deep Learning

Bayes' theorem

Bayes' theorem (also called Bayes' rule or Bayes' law) is a fundamental theorem of probability theory that describes how to update the probability of a...

MathematicsStatistics

Bayesian Neural Network

A Bayesian neural network (BNN) is a neural network in which the weights and biases are represented as probability distributions rather than fixed point...

Deep LearningNeural Networks

Bayesian Optimization

See also: Machine learning terms, Hyperparameter tuning, AutoML Bayesian optimization is a sequential, model-based strategy for finding the global optimum of...

Training & Optimization

Bayesian inference

Bayesian inference is a method of statistical inference in which Bayes' theorem is used to update the probability of a hypothesis as new evidence or data...

Statistics

Bayesian network

A Bayesian network (also called a belief network, Bayes net, directed graphical model, or probabilistic causal network) is a probabilistic graphical model that...

Statistics

Bellman Equation

See also: reinforcement learning, Markov decision process, Q-learning, dynamic programming, value function, Machine learning terms The Bellman equation is a...

MathematicsReinforcement Learning

Best-of-N sampling

Best-of-N sampling (BoN) is an inference-time method that improves a large language model output by drawing N independent candidate responses to the same...

Reinforcement Learning

Bias

Bias in artificial intelligence carries three distinct technical meanings: a learnable scalar parameter added inside a neuron, the systematic error component...

AI EthicsNeural Networks