Machine Learning

Pre-training

Pre-training is the first and most compute-intensive stage of building a modern AI model: a neural network is trained on a massive, mostly unlabeled dataset...

Artificial IntelligenceComputer Vision

Precision

Precision is a classification metric defined as the fraction of positive predictions that are correct: Precision = TP / (TP + FP), where TP is the number of...

Model Evaluation

Precision-Recall Curve

A precision-recall curve (PR curve) is a graph that plots precision on the y-axis against recall on the x-axis at every possible classification threshold for a...

Model Evaluation

Prediction

Prediction in machine learning is the output a trained model produces when it is applied to new, previously unseen input. A prediction can take three main...

Prediction Bias

Prediction bias is the difference between the average of a machine learning model's predictions and the average of the ground-truth labels in a dataset. Stated...

Model Evaluation

Predictive Parity

Predictive parity is a group fairness metric in machine learning that holds when a classifier's positive predictive value (PPV), also called precision, is...

AI Ethics

Predictive rate parity

Predictive rate parity (PRP), also called predictive parity, predictive value parity, or the sufficiency criterion, is a group fairness metric in machine...

AI Ethics

Prefix caching (automatic prefix caching)

Prefix caching is an inference optimization for large language model serving that stores and reuses the key-value (KV) cache computed for a shared prompt...

AI Infrastructure

Preprocessing

Preprocessing is the stage of a machine learning workflow that transforms raw data into a clean, consistent, numerical format that learning algorithms can use....

Data & Datasets

Principal Component Analysis (PCA)

Principal component analysis (PCA) is an unsupervised learning technique for dimensionality reduction that identifies the orthogonal directions of maximum...

MathematicsStatistics

Prior belief

See also: Bayes' theorem, Bayesian inference, Posterior, Likelihood A prior belief, also called the prior distribution or simply the prior, is the probability...

Statistics

Probabilistic Regression Model

A probabilistic regression model (also called distributional regression) is a regression model that outputs a full probability distribution over possible...

Statistics

Process reward model (PRM)

A process reward model (PRM), also called a process-supervised reward model or step-level verifier, is a learned scoring model that evaluates the correctness...

AI SafetyModel Evaluation

Prompt Caching

Prompt caching is an large language model (LLM) inference optimization that stores the computed key-value (KV) state of a repeated prompt prefix so it can be...

Large Language Models

Prompt Engineering

Prompt engineering is the practice of designing, structuring, and refining the text inputs (prompts) given to a generative AI model so that it produces a...

Large Language ModelsNatural Language Processing

Prompt lookup decoding

Prompt lookup decoding (PLD), also called n-gram speculative decoding, is an inference acceleration method for large language models that speeds up text...

AI Infrastructure

Protein folding

Protein folding is the physical process by which a polypeptide chain, a linear sequence of amino acids, acquires its functional three-dimensional structure,...

Artificial Intelligence

Proximal Policy Optimization (PPO)

Proximal Policy Optimization (PPO) is an on-policy policy gradient reinforcement learning algorithm that stabilizes training by clipping the policy update so...

Reinforcement LearningTraining & Optimization

Proxy labels

A proxy label (also called a surrogate label) is an observable, easy-to-collect stand-in for the true target a model should predict, used to train that model...

Data & Datasets

Pruning

Pruning is a family of techniques used in machine learning and artificial intelligence to remove parts of a model or search space that are estimated to be...

AI InferenceTraining & Optimization

PyTorch

PyTorch is an open-source machine learning framework, primarily developed by Meta AI and now governed by the PyTorch Foundation under the Linux Foundation,...

Deep LearningDeveloper Tools

Q-Function

The Q-function, also called the action-value function or state-action value function and written , is the function in reinforcement learning (RL) that returns...

Reinforcement Learning

Q-Learning

See also: Machine learning terms Q-learning is a model-free, off-policy reinforcement learning algorithm that learns the value of taking a given action in a...

Reinforcement Learning

QuIP / QuIP#

QuIP (Quantization with Incoherence Processing) is a family of weight-only post-training quantization methods for large language models developed in the...

AI Infrastructure

Quantile

A quantile is a cut point that divides a probability distribution or a sorted dataset into intervals containing equal portions of the probability or the...

Statistics

Quantile bucketing

See also: Discretization, Feature engineering, Quantile Quantile bucketing, also called quantile binning, equal-frequency binning, or quantile discretization,...

Data & Datasets

Quantization

Quantization in machine learning and artificial intelligence is the process of reducing the numerical precision of a neural network's parameters (weights,...

AI InferenceDeep Learning

Quantization-Aware Training (QAT)

Quantization-aware training (QAT) is a model compression technique in which the effects of quantization are simulated during the training or fine-tuning of a...

AI Infrastructure

Quantum machine learning

Quantum machine learning (QML) is a research field that sits at the intersection of quantum computing and machine learning. The term refers to two...

Artificial IntelligenceComputer Science

Question answering

Question answering (QA) is a subfield of natural language processing and information retrieval in which a computer system automatically produces a direct...

Information RetrievalNatural Language Processing

Queue

A queue in machine learning is a First-In-First-Out (FIFO) data structure that stages and buffers data between an input/output stage and a compute stage so...

Quiet-STaR

Quiet-STaR is a self-supervised training method that teaches a large language model to generate short, token-level internal "thoughts," or rationales, that...

Reinforcement Learning

R (programming language)

R is a free, open-source programming language and software environment for statistical computing and graphics. It was created by Ross Ihaka and Robert...

Programming LanguagesStatistics

RAPTOR

RAPTOR (Recursive Abstractive Processing for Tree-Organized Retrieval) is a retrieval method for retrieval-augmented generation introduced in a 2024 paper by...

AI Agents

RLAIF

Reinforcement Learning from AI Feedback (RLAIF) is a family of alignment techniques for large language models in which the preference labels used to fine-tune...

AI SafetyReinforcement Learning

ROC (Receiver Operating Characteristic) Curve

A Receiver Operating Characteristic (ROC) curve is a graph that measures how well a binary classification system separates two classes by plotting its true...

Model Evaluation

ROUGE

ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is a set of automatic metrics that score the quality of a machine-generated text summary by counting...

Model EvaluationNatural Language Processing

RWKV

RWKV (pronounced "RwaKuv") is an open-source neural network architecture that combines the parallelizable training of Transformers with the constant-time,...

Deep LearningModel Architecture

Random Forest

See also: Machine learning terms A random forest is a supervised machine learning algorithm that builds many decision trees on random subsets of the data and...

Random Policy

See also: Reinforcement Learning, Policy, Epsilon Greedy Policy, Q-Learning A random policy is a reinforcement learning policy that chooses actions from a...

Reinforcement Learning

Rank (Tensor)

In machine learning and deep learning frameworks, the rank of a tensor is the number of dimensions (axes) it has: the count of indices you must supply to pick...

Ranking

Ranking in machine learning, often called learning to rank (LTR), is the supervised task of ordering a set of items by relevance to a query, producing a ranked...

Information Retrieval

Ray (framework)

Ray is an open-source distributed computing framework, developed at the University of California, Berkeley's RISELab and commercialized by Anyscale, that lets...

AI InfrastructureDeveloper Tools

ReLU

See also: Machine learning terms ReLU (Rectified Linear Unit) is an activation function used in neural networks, defined by the formula : it passes positive...

Deep LearningNeural Networks

ReST / ReST-EM (Reinforced Self-Training)

ReST (Reinforced Self-Training) is a family of self-training algorithms for large language models that improve a model by fine-tuning it on its own filtered...

Reinforcement Learning

Reasoning (artificial intelligence)

Reasoning in artificial intelligence is the ability of an AI system to draw inferences, solve problems, and make decisions through structured, multi-step...

Artificial IntelligenceLarge Language Models

Reasoning models

Reasoning models are a class of large language models trained, typically through reinforcement learning on long chain-of-thought traces, to perform an extended...

Artificial IntelligenceLarge Language Models

Recall (metric)

Recall is a classification and retrieval metric that measures the proportion of actual positive instances a model correctly identifies, defined as TP / (TP +...

Model Evaluation

Recommendation System

A recommendation system (also called a recommender system) is an information filtering system that predicts a user's preferences and ranks the items most...

Recommender System

A recommender system (also called a recommendation system or recommendation engine) is an information filtering system that predicts the preference a user...

AI Tools & ProductsInformation Retrieval

Rectified Linear Unit (ReLU)

See also: Activation function, Deep learning, Neural network The Rectified Linear Unit (ReLU) is the most widely used activation function in deep learning,...

Deep LearningNeural Networks

Recurrent Neural Network

See also: Machine learning terms A recurrent neural network (RNN) is a class of artificial neural network designed to process sequential data by maintaining an...

Deep LearningModel Architecture

Recursive self-improvement

Recursive self-improvement (RSI) is a process in which an artificial intelligence system improves its own intelligence or its ability to improve itself, so...

AI SafetyArtificial Intelligence

RedPajama

RedPajama is a family of large-scale, openly licensed datasets for training large language models (LLMs), created by Together AI with academic and open-source...

Data & DatasetsNatural Language Processing

Reflection AI

Private company Industry March 2024 Founders 300 Kent Avenue, Brooklyn, New York, United States Offices Misha Laskin (CEO), Ioannis Alexandros...

AI Companies

Reflexion

Reflexion is a 2023 framework for reinforcing language agents through verbal self-reflection rather than weight updates: the agent reflects in natural language...

AI AgentsReasoning Models

Regression (statistics and machine learning)

Regression is a family of statistical and machine learning methods for modelling the relationship between a numeric outcome variable and one or more...

Statistics

Regularization

Regularization is a set of techniques used in machine learning to prevent overfitting by adding constraints or penalties during training that discourage a...

Deep LearningTraining & Optimization

Regularization Rate

The regularization rate (commonly denoted as or alpha) is a hyperparameter that controls the strength of the penalty applied to a model's parameters during...

Training & Optimization

Reinforcement Learning from Human Feedback (RLHF)

Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that trains artificial intelligence systems to behave according to human...

AI AlignmentDeep Learning