Thursday, July 23, 2026
- RNNv9RNN is the standard abbreviation for recurrent neural network, a class of artificial neural network in which connections between units form cycles
- 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 positive rate (TPR, also called sensitivity or…
- Re-rankingv4Re-ranking, also written as reranking, is the second stage of a two-stage information retrieval pipeline: a fast first-stage retriever returns a candidate set of roughly 50 to 1000 documents
- Real Estate ChatGPT Pluginsv4Real Estate ChatGPT Plugins were a topical grouping inside the ChatGPT plugin catalogue that gathered third-party extensions oriented toward residential property search, rental listings, and neighborhood…
- Rank (ordinality)v5In machine learning and statistics, rank or ordinality describes data whose values have a meaningful order but whose spacing between values is not necessarily equal or quantitatively meaningful.
- 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 quantum logic operations.
- Rankingv5Ranking in machine learning, often called learning to rank (LTR), is the supervised task of ordering a set of items by relevance to a query
- Queuev4A 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 that elements are processed in the order they were…
- Predictionv6Prediction in machine learning is the output a trained model produces when it is applied to new, previously unseen input.
- Predictive Parityv5Predictive parity is a group fairness metric in machine learning that holds when a classifier's positive predictive value (PPV), also called precision
- 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 principles of quantum mechanics to perform…
- AI presentation toolsv5AI presentation tools are software products that use generative AI to create or assist in building slide decks.
- 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 binary classification model.
- 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 plain language instead of an editor or a…
- Q-Learningv9Q-learning is a model-free, off-policy reinforcement learning algorithm that learns the value of taking a given action in a given state by iteratively updating an action-value function Q(s, a), the expected…
- Preprocessingv5Preprocessing is the stage of a machine learning workflow that transforms raw data into a clean, consistent, numerical format that learning algorithms can use.
- Predictive rate parityv6Predictive rate parity (PRP), also called predictive parity, predictive value parity, or the sufficiency criterion, is a group fairness metric in machine learning that requires a classifier's positive…
- Prior beliefv4A prior belief, also called the prior distribution or simply the prior, is the probability distribution that expresses what is known or assumed about an unknown parameter before any data is observed.
- Probabilistic Regression Modelv7A probabilistic regression model (also called distributional regression) is a regression model that outputs a full probability distribution over possible target values rather than a single point estimate.
- Q-Functionv8The Q-function, also called the action-value function or state-action value function and written $$Q(s, a)$$, is the function in reinforcement learning (RL) that returns the expected cumulative discounted…
- Productivity ChatGPT Pluginsv4Productivity ChatGPT Plugins were a now-deprecated category of third-party extensions inside ChatGPT that connected the chatbot to external work tools such as task managers, email, calendars, file storage…
- 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.
- Programming Custom GPTsv5Programming Custom GPTs are no-code, specialized versions of ChatGPT that users configure to write, debug, review, explain, and teach code, published in the Programming category of the GPT Store.
- Pipelinev4A pipeline in machine learning is a sequence of data processing steps chained together into an automated, end-to-end workflow, where each step takes the previous step's output as its input.
- Photographyv4Artificial intelligence in photography covers a wide span of techniques, from the computational pipelines baked into modern smartphones to the generative editing tools now built into Photoshop and Lightroom…
- 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 narration tools, and listening recommendation…
- Photography ChatGPT Pluginsv4Photography ChatGPT Plugins were a small group of third-party extensions inside ChatGPT that helped the chatbot work with photographs, photographic filters, and prompts used to produce photography-style…
- Post-processingv5In machine learning, post-processing is any operation applied to a model's raw outputs after the prediction step but before the results reach a downstream system or end user.
- Poolingv8Pooling is a downsampling operation in neural networks that aggregates each local region of a feature map into a single summary value
- PoisonGPTv3PoisonGPT is a July 2023 demonstration by the French security startup Mithril Security in which researchers surgically modified an open-source large language model, uploaded the tampered weights to Hugging…
- 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 feature extractor or by fine-tuning
- 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 records, and political document archives between…
- Pipeliningv8Pipelining is a term used in two distinct senses within machine learning and artificial intelligence.
- Policyv7In reinforcement learning (RL), a policy is the function that maps an agent's observed state to the action it takes, defining the agent's complete strategy of behavior.
- Positive classv5In binary classification, the positive class is the class a model is testing for: the outcome it exists to detect, such as "spam," "fraud," or "tumor." The other label, covering everything else
- 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, instruction-following AI assistant.
- AI in politicsv3Artificial intelligence has become an established part of modern political work, used by campaigns, governments, journalists, and ordinary citizens.
- Podcastsv4AI podcasts are audio shows about artificial intelligence: long form research interviews, daily news roundups, and conversations with the founders, scientists, and investors building the technology.
- Precisionv9Precision is a classification metric defined as the fraction of positive predictions that are correct: Precision = TP / (TP + FP), where TP is the number of true positives and FP is the number of false…
- 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 injects continuous sensor and image observations…
- Output Layerv11The output layer is the final layer of a neural network: it takes the features computed by the hidden layers and converts them into the model's prediction, with its size and activation function fixed by the…
- Paper2Videov6Paper2Video (full title: Paper2Video: Automatic Video Generation from Scientific Papers) is a research project from Show Lab at the National University of Singapore that formalizes and evaluates automatic…
- Parameterv6In machine learning and statistics, a parameter is an internal variable of a model whose value is learned from data during the training process.
- Papersv6The most influential AI research papers are the small set of publications that introduced the architectures, training methods, and benchmarks that every modern system is built on, from "Attention Is All You…
- Out-of-bag evaluation (OOB evaluation)v7Out-of-bag (OOB) evaluation, sometimes called out-of-bag estimation or OOB error, is a model validation technique used with bagging-based ensemble methods such as random forests and bagged decision trees.
- 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 similar to one another than members of their own…
- Oversamplingv6Oversampling is a data preprocessing technique in machine learning that fixes class imbalance by increasing the number of minority class examples in the training set, either by duplicating existing samples…
- Partial derivativev7A partial derivative measures how a multivariable function changes when one of its inputs is varied while every other input is held fixed.
- Partitioning strategyv4A partitioning strategy in distributed deep learning is the plan that decides how a model and its training data are split across multiple accelerators (typically GPUs or TPUs) so that the workload can be…
- 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 meaningful ways from those who do not, so the resulting…
- Parameter Server (PS)v6The Parameter Server (PS) is a distributed system architecture for training large machine learning models in which one set of machines, the server nodes, holds the global model parameters as a partitioned…
- Perceptronv7A perceptron is the earliest trainable artificial neural network: a single-layer linear model that classifies inputs into two categories by computing a weighted sum and applying a step threshold.
- 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 to have been generated by a different process.
- Permutation variable importancesv5Permutation variable importance is a model-agnostic technique that measures how much a fitted machine learning model relies on a given feature by randomly shuffling that feature's values and recording how much…
- Performancev4Performance in machine learning is an overloaded word. It refers to two related but distinct ideas. The first is the quality of a model's predictions: how accurate or useful its outputs are for a given task.
- Pandasv6Pandas is an open-source data analysis and manipulation library for the Python programming language, providing high-performance, flexible data structures designed for working with structured (tabular…
- Parameter updatev6A parameter update is the step in neural-network training where a model's trainable weights are adjusted using the gradient of the loss
- Objectivev8In machine learning, an objective (or objective function) is the scalar function that a learning algorithm optimizes during training: the single number whose gradients drive every parameter update.
- Organizationsv6Organizations that build, fund, govern, and study artificial intelligence span private companies, government agencies, university laboratories, non-profit research institutes, and international standards…
- Objective functionv6An objective function is the single scalar-valued quantity that an optimization algorithm tries to minimize or maximize during training.
- 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.
- OpenMulev4OpenMule is an open-source proposal for a decentralized marketplace platform designed to facilitate transactions between end-users and service providers of automated agents.
- Oblique conditionv5An oblique condition is a decision tree split test that involves more than one feature, comparing a linear combination of several numerical features to a threshold rather than testing a single feature on its…
- OpenAI Pulsev4ChatGPT Pulse is a proactive personalized briefing feature within ChatGPT, an artificial intelligence chatbot developed by OpenAI.
- Online learningv7Online learning is a machine learning paradigm in which a model receives data sequentially, one example or one mini-batch at a time, and updates its parameters immediately after each observation rather than…
- OCR Modelsv7OCR Models are artificial intelligence (AI) systems that convert images of typed, handwritten, or printed text into machine-readable digital text through Optical Character Recognition (OCR).
- One-vs.-allv6One-vs.-all (OvA), also known as one-vs.-rest (OvR) or one-against-all, is a strategy for turning a multi-class classification problem into several binary classification problems by training one binary…
- Offlinev5In machine learning, offline describes operations that happen ahead of time on a fixed dataset rather than continuously on live data.
- Numerical Datav6Numerical data (also called quantitative data) is information expressed as numbers on a continuous or discrete scale that supports arithmetic operations such as addition, subtraction, multiplication, and…
- Operation (op)v8In machine learning, an operation (often abbreviated as op) is a basic computational unit that manipulates data, typically tensors, during the training or execution of a model.
- Ollamav11Ollama is a free, open-source runtime for downloading, running, and managing open-weight large language models (LLMs) locally on personal computers and servers.
- Optimizerv8An optimizer in machine learning is an algorithm that iteratively adjusts a model's learnable parameters to minimize (or maximize) an objective function, commonly called a loss function
- One-Hot Encodingv8One-hot encoding is a data preprocessing technique that converts a categorical variable with $$k$$ distinct categories into $$k$$ binary columns, where each category is represented by a vector that contains…
- Offline inferencev7Offline inference (also called batch inference, static inference, or bulk scoring) is the practice of running a trained machine learning model over a known set of inputs ahead of time and storing the resulting…
- Non-binary conditionv4In decision tree learning, a non-binary condition is a test at a node that has more than two possible outcomes, routing each example to one of three or more child nodes and creating a multi-way split.
- Negative classv6In binary classification, the negative class is the outcome the model treats as the default or "no" result: the label assigned to instances that do not possess the target characteristic the model is testing…
- 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 brains
- 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 aggregators between March 2023 and April 2024.
- Natural Language Understandingv8Natural language understanding (NLU) is the branch of artificial intelligence and computational linguistics that enables machines to read human language and extract its meaning, intent, and structure.
- Node (neural network)v8A node in a neural network is the basic computational element, an artificial neuron, that receives one or more inputs, multiplies each by a learned weight, sums them, adds a bias, and passes the result through…
- Novelty Detectionv6Novelty detection is a branch of machine learning concerned with identifying test data that differ in some meaningful way from the data available during training.
- Non-Response Biasv5Non-response bias is the error that arises when the people or units that do not respond to a survey, study, or data collection process differ systematically from those that do
- Normalizationv7Normalization is the process of scaling numerical data to a standard range or distribution so that features and activations are comparable and downstream computation behaves predictably.
- Nonstationarityv6Nonstationarity refers to the condition in which the statistical properties of a data-generating process change over time.
- Noisev6Noise in machine learning is any unwanted, irrelevant, or random variation in data that obscures the true underlying patterns a model is trying to learn.
- NumPyv7NumPy (short for Numerical Python) is the foundational open-source library for numerical and scientific computing in Python, providing an n-dimensional array object called ndarray along with a large collection…
- Node (TensorFlow graph)v5A node in a TensorFlow graph is a single unit of computation, such as a matrix multiplication, an addition, an activation, or a variable read, that occupies one vertex of the framework's computational graph…
- AI in journalismv4AI in journalism refers to the use of artificial intelligence, and especially machine learning and generative AI, in the gathering, production, distribution and verification of news.
- Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers (VALL-E)v6VALL-E is a zero-shot learning text-to-speech (TTS) system from Microsoft Research that clones a target voice from a 3-second recording and synthesizes new speech in that voice without any per-speaker training.
- Nonlinearv7Nonlinear describes any function, model, or relationship that does not satisfy the property of linearity.
- Non-profit Organizationsv4Non-profit organizations active in artificial intelligence are mission-driven entities that conduct research, set standards, advocate for policy, and provide education without returning surplus revenue to…
- Node (decision tree)v4A node is the basic building block of a decision tree: it is a single point in the tree that is either a condition (an internal node that tests a feature and branches) or a leaf (a terminal node that holds a…
- Neuronv4A neuron (also called a node or unit) is the fundamental computational element of an artificial neural network: it takes one or more numeric inputs, multiplies each by a learned weight, sums them with a bias…
- NaN Trapv9A NaN trap (short for "Not a Number" trap) is a failure mode in machine learning training where arithmetic operations produce the special IEEE 754 value NaN, which then propagates through all subsequent…
- Multi-Class Logistic Regressionv6Multi-class logistic regression, also known as multinomial logistic regression, softmax regression, or the maximum entropy (MaxEnt) classifier
- N-gramv6An n-gram is a contiguous sequence of n items extracted from a given sample of text or speech, where the items can be characters, syllables, words, or other linguistic units.
- Multinomial regressionv5Multinomial regression is a statistical model that predicts which one of K possible categories an observation belongs to, given a vector of input features.
- Multi-Class Classificationv6Multi-class classification is a supervised learning task in machine learning that assigns each input to exactly one of three or more mutually exclusive classes.
- Multinomial classificationv5Multinomial classification, also called multiclass or multi-class classification, is the supervised learning task of assigning each input to exactly one of K possible classes, where K is greater than two.
- Music ChatGPT Pluginsv4Music ChatGPT plugins were a category of third-party extensions for ChatGPT that let the chatbot generate streaming playlists, recommend and surface songs, convert music notation to audio and sheet music…
