Thursday, July 23, 2026
- Rank (Tensor)v4See also: Machine learning terms In machine learning and deep learning frameworks, the rank of a tensor is the number of dimensions (axes) it has: the count of...
- Raterv5See also: Machine learning terms A rater is a person (or, increasingly, a model) who assigns labels, scores, or judgments to data items so those items can be...
- Quantilev4See also: Machine learning terms A quantile is a cut point that divides a probability distribution or a sorted dataset into intervals containing equal portions...
- RNNv9See also: Machine learning terms RNN is the standard abbreviation for recurrent neural network, a class of artificial neural network in which connections...
- ROC (Receiver Operating Characteristic) Curvev8A Receiver Operating Characteristic (ROC) curve is a graph that measures how well a binary classification system separates two classes by plotting its true...
- Qwenv10Qwen is a family of open-source and proprietary large language models (LLMs) and multimodal models developed by Alibaba Cloud, the cloud computing division of...
- Re-rankingv4See also: Machine learning terms, Ranking, Information Retrieval Re-ranking, also written as reranking, is the second stage of a two-stage information...
- Real Estate ChatGPT Pluginsv4See also: ChatGPT Plugins, ChatGPT Plugin Categories and Real Estate Real Estate ChatGPT Plugins were a topical grouping inside the ChatGPT plugin catalogue...
- Rank (ordinality)v5See also: Machine learning terms In machine learning and statistics, rank or ordinality describes data whose values have a meaningful order but whose spacing...
- ReLUv10See also: Machine learning terms ReLU (Rectified Linear Unit) is an activation function used in neural networks, defined by the formula : it passes positive...
- Random Forestv11See 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...
- Quantum processorv5A quantum processing unit (QPU), also called a quantum processor, is the hardware component of a quantum computer that holds and manipulates qubits to perform...
- Rankingv5See also: Information retrieval, Re-ranking, Recommendation system Ranking in machine learning, often called learning to rank (LTR), is the supervised task of...
- Queuev4See also: Machine learning terms A queue in machine learning is a First-In-First-Out (FIFO) data structure that stages and buffers data between an input/output...
- Programmingv8AI for programming refers to the use of artificial intelligence, and especially large language models, to write, edit, refactor, test, review, and explain...
- Predictionv6See also: Machine learning terms Prediction in machine learning is the output a trained model produces when it is applied to new, previously unseen input. A...
- Predictive Parityv5Predictive parity is a group fairness metric in machine learning that holds when a classifier's positive predictive value (PPV), also called precision, is...
- QPUv7A Quantum Processing Unit (QPU), also known as a quantum processor, is the core hardware component of a quantum computer that manipulates qubits using the...
- Productivity Custom GPTsv5See also: Custom GPTs, GPT Store and ChatGPT "Increase your efficiency" , Official Description Productivity Custom GPTs are the category of user-built Custom...
- AI presentation toolsv5AI presentation tools are software products that use generative AI to create or assist in building slide decks. Given a short text prompt, a topic, an uploaded...
- Precision-Recall Curvev8A 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...
- Programming with ChatGPTv5Programming with ChatGPT is the practice of using OpenAI's conversational chatbot to read, write, refactor, document, debug, test, and explain source code in...
- Q-Learningv9See 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...
- Preprocessingv5See also: Machine learning terms, Feature engineering, Data augmentation Preprocessing is the stage of a machine learning workflow that transforms raw data...
- Predictive rate parityv6Predictive rate parity (PRP), also called predictive parity, predictive value parity, or the sufficiency criterion, is a group fairness metric in machine...
- Prior beliefv4See also: Bayes' theorem, Bayesian inference, Posterior, Likelihood A prior belief, also called the prior distribution or simply the prior, is the probability...
- Productivityv7Productivity in the context of artificial intelligence refers to the use of AI software to help individuals and organizations get more work done in less time,...
- Probabilistic Regression Modelv7A probabilistic regression model (also called distributional regression) is a regression model that outputs a full probability distribution over possible...
- Q-Functionv8The Q-function, also called the action-value function or state-action value function and written , is the function in reinforcement learning (RL) that returns...
- Q* OpenAIv5Q (pronounced Q-Star) is the reported, never-officially-detailed OpenAI research project that surfaced in news reports during the November 2023 leadership...
- Productivity ChatGPT Pluginsv4See also: ChatGPT Plugins, ChatGPT Plugin Categories and Productivity Productivity ChatGPT Plugins were a now-deprecated category of third-party extensions...
- Prediction Biasv4Prediction 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...
- Programming ChatGPT Pluginsv4See also: ChatGPT Plugins, Software Development ChatGPT Plugins, ChatGPT Plugin Categories and Programming Programming ChatGPT Plugins were a now-deprecated...
- Programming Custom GPTsv5See also: Custom GPTs, GPT Store, ChatGPT, and OpenAI Programming Custom GPTs are no-code, specialized versions of ChatGPT that users configure to write,...
- Pluginsv7Plugins are modular software extensions that connect large language models and other AI systems to external tools, services, data sources, and user interfaces,...
- Pipelinev4See also: Machine learning, MLOps, Model deployment This article is about machine learning pipelines (the end-to-end ML workflow). For splitting a model across...
- Photographyv4See also: Photography ChatGPT Plugins Artificial intelligence in photography covers a wide span of techniques, from the computational pipelines baked into...
- Perplexityv10Perplexity has two distinct meanings in the field of artificial intelligence. In natural language processing and information theory, perplexity (often...
- Podcasts ChatGPT Pluginsv3Podcasts ChatGPT plugins were a category of third-party extensions for ChatGPT that connected the chatbot to podcast search engines, episode transcripts, audio...
- Photography ChatGPT Pluginsv4See also: ChatGPT Plugins, ChatGPT Plugin Categories and Photography Photography ChatGPT Plugins were a small group of third-party extensions inside ChatGPT...
- Post-processingv5See also: Machine learning terms In machine learning, post-processing is any operation applied to a model's raw outputs after the prediction step but before...
- Poolingv8See also: convolutional neural network, convolutional layer, feature map, downsampling Pooling is a downsampling operation in neural networks that aggregates...
- PoisonGPTv3PoisonGPT is a July 2023 demonstration by the French security startup Mithril Security in which researchers surgically modified an open-source large language...
- Pre-Trained Modelv7A pre-trained model is a machine learning model that has already been trained on a large, general-purpose dataset and can then be reused, either as a fixed...
- Politics ChatGPT Pluginsv4Politics ChatGPT plugins were a small set of third-party tools that connected ChatGPT to legislative data, voting records, lobbying disclosures, party donation...
- Pipeliningv8See also: Machine learning terms Pipelining is a term used in two distinct senses within machine learning and artificial intelligence. The first refers to the...
- Pre-trainingv6Pre-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...
- Policyv7See also: Reinforcement learning, Q-learning, Markov decision process In reinforcement learning (RL), a policy is the function that maps an agent's observed...
- Positive classv5See also: Machine learning terms In binary classification, the positive class is the class a model is testing for: the outcome it exists to detect, such as...
- Post-trainingv7Post-training is the stage of large language model (LLM) development that comes after pre-training and turns a raw, general-purpose base model into an aligned,...
- AI in politicsv3Artificial intelligence has become an established part of modern political work, used by campaigns, governments, journalists, and ordinary citizens. Its...
- Podcastsv4AI podcasts are audio shows about artificial intelligence: long form research interviews, daily news roundups, and conversations with the founders, scientists,...
- Precisionv9See also: Machine learning terms Precision is a classification metric defined as the fraction of positive predictions that are correct: Precision = TP / (TP +...
- PowerPoint Presentation Maker by SlidesGPTv6--- Information PowerPoint Presentation Maker by SlidesGPT Platform GPT Store Model Writing Description slidesgpt.com OpenAI URL 17,000 ...
- PaLM-E: An Embodied Multimodal Language Modelv5PaLM-E (short for Pathways Language Model, Embodied) is an embodied multimodal large language model introduced by Google and TU Berlin in March 2023 that...
- Overfittingv9See also: Machine learning terms Overfitting is when a machine learning model fits its training set so closely that it learns the noise and quirks of those...
- Output Layerv11See also: neural network, activation function, loss function, hidden layer, softmax, backpropagation The output layer is the final layer of a neural network:...
- Paper2Videov6Paper2Video (full title: Paper2Video: Automatic Video Generation from Scientific Papers) is a research project from Show Lab at the National University of...
- Parameterv6In machine learning and statistics, a parameter is an internal variable of a model whose value is learned from data during the training process.[1] Parameters...
- Outliersv8See also: machine learning terms, anomaly detection, robust statistics, data preprocessing An outlier is a data point that differs so markedly from the rest of...
- Papersv6The most influential AI research papers are the small set of publications that introduced the architectures, training methods, and benchmarks that every modern...
- Out-of-bag evaluation (OOB evaluation)v7See also: Machine learning terms, Bagging, Random forest, Cross-validation Out-of-bag (OOB) evaluation, sometimes called out-of-bag estimation or OOB error, is...
- Out-Group Homogeneity Biasv6Out-group homogeneity bias, also called the out-group homogeneity effect, is the cognitive bias in which people perceive members of an out-group as more...
- Oversamplingv6Oversampling is a data preprocessing technique in machine learning that fixes class imbalance by increasing the number of minority class examples in the...
- Partial derivativev7See also: Machine learning terms A partial derivative measures how a multivariable function changes when one of its inputs is varied while every other input is...
- Partitioning strategyv4See also: Data parallelism, Model parallelism, Pipeline parallelism, Tensor parallelism, Distributed training A partitioning strategy in distributed deep...
- Participation Biasv5Participation bias is a systematic error that arises when the individuals who choose to take part in a study, survey, or data collection effort differ in...
- Parameter Server (PS)v6See also: Distributed training, Machine learning systems The Parameter Server (PS) is a distributed system architecture for training large machine learning...
- Perceptronv7See also: Machine learning terms A perceptron is the earliest trainable artificial neural network: a single-layer linear model that classifies inputs into two...
- Outlier Detectionv7Outlier detection is the process of identifying data points, observations, or patterns that deviate so markedly from the rest of a dataset that they are likely...
- Permutation variable importancesv5See also: Variable importances, Feature engineering, Machine learning terms Permutation variable importance is a model-agnostic technique that measures how...
- Performancev4See also: Machine learning terms Performance in machine learning is an overloaded word. It refers to two related but distinct ideas. The first is the quality...
- Pandasv6See also: Machine learning terms, Data analysis, NumPy Pandas is an open-source data analysis and manipulation library for the Python programming language,...
- Parameter updatev6See also: Machine learning terms A parameter update is the step in neural-network training where a model's trainable weights are adjusted using the gradient of...
- OpenAIv20Public Benefit Corporation (OpenAI Group, formerly OpenAI Global LLC); Non-profit foundation (OpenAI Foundation) Industry December 11, 2015 Founders ...
- Objectivev8See also: Machine learning terms In machine learning, an objective (or objective function) is the scalar function that a learning algorithm optimizes during...
- Organizationsv6See also: Terms, Models, Applications, Companies and Non-profit Organizations Organizations that build, fund, govern, and study artificial intelligence span...
- Objective functionv6See also: Machine learning terms An objective function is the single scalar-valued quantity that an optimization algorithm tries to minimize or maximize during...
- One-Shot Learningv6One-shot learning is a machine learning approach in which a model learns to recognize or classify new categories from only a single labeled example per class....
- OpenMulev4An open-source, decentralized marketplace for AI and physical automation agent services. Abbreviation vibe-coded-marketplace (February 25, 2026) Authors ...
- Oblique conditionv5See also: Machine learning terms An oblique condition is a decision tree split test that involves more than one feature, comparing a linear combination of...
- OpenAI Pulsev4ChatGPT Pulse is a proactive personalized briefing feature within ChatGPT, an artificial intelligence chatbot developed by OpenAI. Launched in preview on...
- Online learningv7See also: Machine learning terms Online learning is a machine learning paradigm in which a model receives data sequentially, one example or one mini-batch at a...
- OCR Modelsv7OCR Models are artificial intelligence (AI) systems that convert images of typed, handwritten, or printed text into machine-readable digital text through...
- One-vs.-allv6See also: Machine learning terms One-vs.-all (OvA), also known as one-vs.-rest (OvR) or one-against-all, is a strategy for turning a multi-class classification...
- Offlinev5See also: Machine learning terms In machine learning, offline describes operations that happen ahead of time on a fixed dataset rather than continuously on...
- Numerical Datav6See also: Categorical data, Feature engineering, Data preprocessing Numerical data (also called quantitative data) is information expressed as numbers on a...
- Operation (op)v8See also: Machine learning terms In machine learning, an operation (often abbreviated as op) is a basic computational unit that manipulates data, typically...
- OpenRouterv10OpenRouter is a unified API gateway and marketplace that routes a single, OpenAI-compatible request across more than 400 large language models (LLMs) and other...
- Ollamav11Ollama is a free, open-source runtime for downloading, running, and managing open-weight large language models (LLMs) locally on personal computers and...
- Optimizerv8An optimizer in machine learning is an algorithm that iteratively adjusts a model's learnable parameters to minimize (or maximize) an objective function,...
- One-Hot Encodingv8See also: Machine learning terms One-hot encoding is a data preprocessing technique that converts a categorical variable with distinct categories into ...
- Online inferencev7See also: offline inference, static inference, dynamic inference, inference, machine learning terms Online inference (also called dynamic inference, real-time...
- Offline inferencev7See also: online inference, static inference, dynamic inference, inference, machine learning terms Offline inference (also called batch inference, static...
- Non-binary conditionv4See also: Machine learning terms In decision tree learning, a non-binary condition is a test at a node that has more than two possible outcomes, routing each...
- Negative classv6See also: Machine learning terms In binary classification, the negative class is the outcome the model treats as the default or "no" result: the label assigned...
- Neural Networkv11A neural network (also called an artificial neural network or ANN) is a computational model, loosely inspired by the networks of biological neurons in animal...
- News ChatGPT Pluginsv4News ChatGPT plugins were a category of third-party tools that connected ChatGPT to live news feeds, breaking headlines, regional outlets, and topic-specific...
- Natural Language Understandingv8See also: Machine learning terms, Natural language processing, Sentiment analysis Natural language understanding (NLU) is the branch of artificial intelligence...
- Node (neural network)v8See also: Machine learning terms A node in a neural network is the basic computational element, an artificial neuron, that receives one or more inputs,...
