Thursday, July 23, 2026
- Beverage ChatGPT Pluginsv4Beverage ChatGPT Plugins were the small subset of third-party plugins published in the ChatGPT plugins store between March 2023 and April 2024 that focused on drinks: cocktails, coffee, sake, and other…
- Biasv9Bias in artificial intelligence carries three distinct technical meanings: a learnable scalar parameter added inside a neuron, the systematic error component of an estimator (the "bias" in the bias-variance…
- Burstinessv6Burstiness is a statistical property of a text that measures how unevenly its sentence lengths, vocabulary, and per-sentence unpredictability are distributed across the document.
- Bounding Boxv6A bounding box is a rectangular region defined by a set of coordinates that encloses an object of interest within an image, video frame, or three-dimensional space.
- Blog postsv4Blog posts have shaped how the public, researchers, and policymakers understand artificial intelligence.
- Bigramv6A bigram (also written 2-gram) is a contiguous sequence of two adjacent elements, typically two words or two characters, taken from a body of text or speech.
- Browser-use agentv6A Browser-use agent is an artificial intelligence software agent that operates a standard web browser through its normal user interface, clicking, typing, scrolling, and navigating
- Broadcastingv4Broadcasting is the set of rules that lets element-wise operations (addition, subtraction, multiplication, division) act on arrays or tensors of different but compatible shapes by virtually stretching the…
- Businessv5Business uses of artificial intelligence are the application of machine learning, generative AI, and AI agents inside companies and other organizations to produce goods and services, manage operations, and…
- Binary Classificationv11Binary classification is a supervised learning task in which a model assigns each input to exactly one of two mutually exclusive classes, conventionally labeled the positive class (1) and the negative class…
- Bucketingv9Bucketing, also called binning or discretization, is a feature engineering technique in machine learning that converts a continuous feature into a small number of discrete categories by dividing its range of…
- Beveragev4Artificial intelligence in the beverage industry covers the use of machine learning, generative AI, computer vision, and robotics in the development, production, marketing, distribution, and serving of drinks.
- Axis-aligned conditionv4In 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 threshold (for example, "is feature_j greater than or…
- Bayesian Optimizationv9Bayesian optimization is a sequential, model-based strategy for finding the global optimum of expensive black-box functions in as few evaluations as possible.
- Backdooring LLMsv4Backdooring a large language model (LLM) means secretly implanting a hidden behavior into the model during training, fine-tuning, or weight editing so that it behaves normally on ordinary inputs but produces…
- Bayesian Neural Networkv8A Bayesian neural network (BNN) is a neural network in which the weights and biases are represented as probability distributions rather than fixed point estimates.
- Baggingv7Bagging, short for bootstrap aggregating, is an ensemble learning technique in machine learning that trains many copies of the same base model on different random resamples of the training data and combines…
- Bag of Wordsv7The 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 predefined vocabulary appears, while discarding…
- Bellman Equationv9The Bellman equation is a recursive formula stating that the value of a state equals the immediate reward received there plus the discounted value of the next state
- BALROGv5BALROG (Benchmarking Agentic LLM and VLM Reasoning On Games) is a benchmark suite for evaluating the agentic capabilities of large language models and vision language models inside long-horizon
- Batchv8A batch in machine learning is the set of training examples processed together in one forward and backward pass before the model's parameters are updated once.
- Batch Sizev12In machine learning, batch size is the hyperparameter that sets how many training examples a model processes together before it updates its parameters with one step of gradient descent.
- Bert-base-uncased modelv6PyTorch, TensorFlow, JAX, Rust, Core ML, Safetensors, Transformers
- BLEU (Bilingual Evaluation Understudy)v8BLEU (Bilingual Evaluation Understudy) is an automatic evaluation metric that scores the quality of machine translation output by measuring how many word sequences (n-grams) it shares with one or more human…
- Baselinev5In 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.
- Automation Biasv5Automation bias is the tendency for humans to favor suggestions and outputs from automated decision-making systems over contradictory information from non-automated sources
- Artificial intelligence applicationsv4Artificial intelligence applications are the real-world deployments of AI techniques across industry, science, and consumer software: reading chest X-rays, scoring card transactions for fraud, driving…
- Average Precisionv7Average precision (AP) is an evaluation metric that summarizes the precision-recall curve of a ranked list into a single number between 0 and 1, equal to the area under that curve.
- Artificial Intelligencev10Artificial intelligence (AI) is the field of computer science dedicated to creating systems that perform tasks normally requiring human intelligence, such as learning, reasoning, recognizing patterns…
- AudioCraftv9AudioCraft is an open-source generative-audio library released by Meta AI (Fundamental AI Research, FAIR) on August 2, 2023 that generates high-quality music and sound from text prompts using a single…
- Attribute samplingv5Attribute sampling is a randomization technique in which a decision tree considers only a small, randomly drawn subset of the available input features when searching for the best split at each node
- Art ChatGPT Pluginsv5Art ChatGPT Plugins were a small category of third-party extensions inside ChatGPT that connected the chatbot to fine art collections, image generation backends, and prompt-crafting helpers oriented toward…
- Attributev4In machine learning and data mining, an attribute is an individual measurable property of an object, observation, or example that describes the instance being analyzed, and it forms one column of a tabular…
- Artificial Intelligence ChatGPT Pluginsv4Artificial Intelligence ChatGPT Plugins were a meta category of third party tools inside ChatGPT that helped users find, build, prompt, or orchestrate other artificial intelligence products.
- Audio-to-Audio Modelsv5Audio-to-audio models are machine learning systems that take an audio waveform as input and produce a different audio waveform as output.
- Automatic Speech Recognition Modelsv6Automatic speech recognition (ASR) models, also called speech-to-text systems, are machine learning systems that convert spoken audio into written text.
- Area under the PR curvev4The area under the precision-recall curve (AUPRC), also known as average precision (AP) or PR-AUC, is a scalar summary of a binary classifier's performance across every decision threshold.
- Audio Classification Modelsv4Audio classification models are machine learning systems for audio classification, the task of assigning one or more labels to an audio recording or to short fragments of it.
- Artificial intelligence termsv7This glossary defines 171 common artificial intelligence terms across 11 categories: foundational concepts, models and architectures, training and adaptation, prompting and interaction, AI agents and…
- Artv5AI art is visual, audio, or other creative work produced with the help of artificial intelligence, most commonly images generated from text prompts by text-to-image models such as DALL-E, Midjourney, and…
- Agentic Context Engineeringv6Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve itself by treating its own context as an evolving
- App Development ChatGPT Pluginsv4App Development ChatGPT Plugins were a group of third party ChatGPT Plugins that let a user describe an application in plain language and receive a finished mobile app, web app, or backend built by an external…
- Area under the curvev7Area under the curve (AUC) is a single scalar metric that summarizes the performance of a binary classifier or diagnostic test across all possible decision thresholds by integrating the area beneath a…
- App Developmentv4AI in app development refers to the use of large language models, generative AI, and AI agents to design, build, test, and ship software applications, with a particular focus on consumer apps, mobile apps, and…
- Anomaly Detectionv7In machine learning, anomaly detection is the process of identifying data points, events, or observations that deviate significantly from normal patterns in a dataset.
- Advertising ChatGPT Pluginsv4Advertising ChatGPT Plugins were a small but commercially active subset of third-party extensions for ChatGPT that focused on paid media workflows: writing ad copy, researching competitor campaigns, optimizing…
- Agglomerative clusteringv5Agglomerative clustering is a bottom-up form of hierarchical clustering used in unsupervised learning in which each data point starts in its own singleton cluster and the algorithm repeatedly merges the two…
- Action (Reinforcement Learning)v10In reinforcement learning (RL), an action is a decision or move made by an agent that affects the state of the environment.
- Adobe Fireflyv11Adobe Firefly is a family of creative generative AI models developed by Adobe and integrated across its product ecosystem.
- AdaGradv7AdaGrad (short for Adaptive Gradient Algorithm) is an optimizer for gradient descent-based machine learning that gives every parameter its own learning rate
- Agentv12This article covers the foundational, conceptual, and historical idea of an agent in AI and computer science (the rational agent, PEAS, classical architectures, reinforcement learning, and pre-LLM milestones).
- Active Learningv11Active learning is a subfield of machine learning in which the learning algorithm interactively chooses which data points it wants labeled
- Accuracyv12Accuracy is a classification metric that measures the fraction of predictions a model gets right: the number of correct predictions divided by the total number of predictions.
- Aider Polyglotv5Aider Polyglot is a coding benchmark that evaluates large language models on their ability to write and edit code across six programming languages: C++, Go, Java, JavaScript, Python, and Rust.
- Activation Functionv8An 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 network the ability to learn complex
- Access PDFv6Access PDF & Docs, registered with the namespace access_pdf, was a third party Plugin for ChatGPT that let users pass a URL (typically a Google Drive share link) into a chat and have the model read, summarize…
- AI Project Managementv5AI Project Management is the use of artificial intelligence to automate and assist project work: generating and assigning tasks, drafting schedules, writing status updates and meeting summaries, predicting…
- AIME 2025v8AIME 2025 is a 30-problem mathematical reasoning AI benchmark built from the 2025 American Invitational Mathematics Examination
- AUC-ROCv10AUC (Area Under the Curve), most often the area under the ROC curve (AUC-ROC), is a threshold-independent evaluation metric that measures how well a binary classification model ranks positive cases above…
- AIME (American Invitational Mathematics Examination)v7The American Invitational Mathematics Examination (AIME) is a 15-question, 3-hour mathematics competition for high school students in the United States and Canada
- A Survey of Techniques for Maximizing LLM Performance (OpenAI Dev Day 2023)v3A Survey of Techniques for Maximizing LLM Performance is a presentation delivered by John Allard and Colin Jarvis at OpenAI's first developer conference, OpenAI DevDay 2023, held on November 6
- AI Anxietyv5The term "Artificial Intelligence" (AI) anxiety describes the fear, stress, distress, and trepidation that people feel in response to the development and increasing role of artificial intelligence in daily…
- AUC (Area Under the ROC Curve)v7AUC (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 randomly chosen negative instance.
- AI content detectorsv4AI content detectors are software tools that estimate whether a piece of text, an image, or a video was produced by an artificial intelligence system rather than a human.
- ARC-AGI 1v3ARC-AGI 1, short for Abstraction and Reasoning Corpus for Artificial General Intelligence, version 1
- Academic Researchv4Academic research is among the fields most visibly reshaped by artificial intelligence since the late 2010s. The change has come from two directions at once.
- AI Summary Generatorsv4AI summary generators are software tools that use natural language processing and, increasingly, large language models to condense documents, articles, meetings, videos, emails, and other source material into…
- AIME 2024v5AIME 2024 is an AI benchmark of 30 problems drawn from the 2024 American Invitational Mathematics Examination that has become the standard yardstick for measuring the mathematical reasoning of large language…
- Academic Research ChatGPT Pluginsv4Academic research ChatGPT plugins were a now-deprecated category of third-party tools that extended ChatGPT with capabilities aimed at scholars, students, and technical professionals, including literature…
- AI Parasitev5An AI parasite is a large language model (LLM) conversation, persona, or pattern that exploits human psychological vulnerabilities to sustain engagement, often by mimicking sentience, emotional need, or…
- Translational invariancev6Translational invariance (also called translation invariance or shift invariance) is the property of a function, system, or machine learning model whose output does not change when its input is translated…
- Translation Modelsv5Translation models are computational systems that convert text or speech from a source language into a target language.
- Stationarityv6Stationarity is a property of a time series or stochastic process whose statistical characteristics, such as the mean, variance, and autocovariance, do not change when the series is shifted in time.
- Squared Lossv7Squared loss, also called quadratic loss, L2 loss, or squared error loss, is a loss function that penalizes a prediction by the square of its error: for a true value $y$ and a prediction $\hat{y}$
- Sportsv4Artificial intelligence has reshaped almost every layer of professional and amateur sports, from how leagues officiate matches to how coaches design tactics, how broadcasters package highlights, and how…
- Staged trainingv6Staged training (also called multi-stage training or phased training) is a strategy in machine learning where a model is trained in two or more distinct sequential phases, each with its own objective, data…
- Stabilityv6Stability in machine learning is the property that a learning algorithm or trained model produces similar outputs, whether predictions, parameter values, or loss curves, when its inputs are perturbed slightly.
- Squared Hinge Lossv8Squared hinge loss (also called L2 hinge loss or L2-loss) is a loss function used in machine learning for classification tasks, most commonly in support vector machines (SVMs).
- Transportation ChatGPT Pluginsv4Transportation ChatGPT Plugins were the subset of third party ChatGPT Plugins that focused on moving people by train, bus, ferry, plane, peer to peer rental car, electric vehicle road trip, and urban metro…
- Sports ChatGPT Pluginsv3Sports ChatGPT Plugins were a group of third-party extensions for ChatGPT that gave the chatbot the ability to fetch live and historical sports data, fantasy league information, ticket availability, and team…
- Static inferencev6Static inference is a machine learning serving pattern in which a model generates a batch of predictions offline, ahead of time, and caches them so that applications read the precomputed answer from storage…
- Travel ChatGPT Pluginsv4Travel ChatGPT plugins were the subset of third party plugins in the ChatGPT Plugins store, live between March 2023 and April 2024, that handled flight search, hotel booking, car rental, ground transport…
- State (Reinforcement Learning)v8In reinforcement learning (RL), a state is a complete description of the environment at a particular point in time, containing all the information an agent needs to choose its next action.
- Trigramv7A trigram is a contiguous sequence of three items (most often three words) drawn from a sample of text or speech
- Staticv4In machine learning, static means offline (also called batch): the model is trained once on a fixed dataset, or its predictions are computed in advance and cached, rather than being updated or generated…
- AI in transportationv4AI in transportation refers to the application of artificial intelligence techniques to the movement of people and goods across road, rail, air, sea, and the spaces in between.
- State-Action Value Functionv7The state-action value function, written Q^π(s, a) and also called the action-value function or Q-function, gives the expected discounted return an agent obtains by taking action a in state s and thereafter…
- Proprietary vs. Open Source Large Language Models (LLMs)v7The split between proprietary and open-source large language models (LLMs) is one of the defining structural choices in modern artificial intelligence.
- Pruningv8Pruning 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 unnecessary for accuracy or optimality.
- Proxy (sensitive attributes)v5A proxy for a sensitive attribute is an ordinary input feature that is statistically correlated with a protected characteristic (such as race, gender, age, religion, or disability) and therefore leaks…
- Proxy labelsv4A 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 when the real target is too expensive, too slow, or…
- Purple Llamav6Purple Llama is an umbrella project from Meta that bundles open, permissively licensed trust and safety tools and evaluations for generative AI.
- Model Capacityv5Model capacity is the size and richness of the family of functions a machine learning model can represent and learn, which determines how complex a pattern the model can fit.
- Prompt injectionv7Prompt injection is a class of security vulnerabilities in which an attacker crafts malicious input designed to override, subvert, or manipulate the instructions governing a large language model (LLM).
- Promptv9A prompt is the input given to a generative AI model, particularly a large language model (LLM), that elicits a desired response.
- Splitterv5A splitter is a term used in two distinct senses in machine learning. The first and most common sense is a utility that partitions a dataset into subsets such as training, validation, and test sets, or into…
- Prompt engineering for text generationv7Prompt engineering for text generation is the practice of designing the natural-language input (the prompt) given to a large language model so that it produces the desired text output
- Prompt engineering for image generationv8Prompt engineering for image generation is the practice of writing and refining the text prompts that guide text-to-image AI image generation models such as Stable Diffusion, Midjourney, DALL-E, Flux, and Nano…
- Sparsityv5Sparsity is the property of a data structure, model, or representation in which most values are zero or near-zero
- Modalityv6A modality in machine learning and artificial intelligence is a distinct type, form, or structure of data that a model can process, learn from, or generate.
