Wednesday, March 18, 2026
- GPT Detectorv7GPT Detector is a Custom GPT for ChatGPT listed in the GPT Store. It was published by the developer chatgptbuddy.com and built on top of GPT-4.
- GPT Customizer, File Finder & JSON Action Creatorv8GPT Customizer, File Finder & JSON Action Creator is a Custom GPT for ChatGPT published in the GPT Store.
- GPT APIv7The GPT API is the public HTTP interface that OpenAI exposes for programmatic access to its hosted language, vision, audio, image, and video models.
- GPT-Builders' Assistantv9GPT-Builders' Assistant is a Custom GPT for ChatGPT in the GPT Store, built by the developer profile gendojo.ai.
- GPT-4 Pluginsv9GPT-4 Plugins were a system of optional add-ons offered by OpenAI inside the ChatGPT product that let the underlying GPT-4 model call out to external services, retrieve live information, and perform real-world…
- GPT-4 (Custom GPT)v7GPT-4 is a Custom GPT for ChatGPT published in the GPT Store by an independent builder credited as XIANG SHENG. Despite its name, this Custom GPT is not an official OpenAI product.
- GPT-4v20GPT-4 (Generative Pre-trained Transformer 4) is a large language model developed by OpenAI and released on March 14, 2023.
- GPT-3v15GPT-3 (Generative Pre-trained Transformer 3) is a family of decoder-only, autoregressive large language models developed by OpenAI.
- GPT-2v13GPT-2 is a family of autoregressive language models introduced by OpenAI on February 14, 2019.
- GPT-1v11GPT-1 is the first model in the GPT (Generative Pre-trained Transformer) series, a 117-million-parameter, 12-layer decoder-only Transformer released by OpenAI on June 11, 2018 in the paper "Improving Language…
- GPTv13GPT, short for Generative Pre-trained Transformer, is the name of a model family developed by OpenAI.
- GPQA Diamondv10GPQA Diamond is the 198-question hardest subset of the Graduate-Level Google-Proof Q&A Benchmark (GPQA), a set of PhD-level multiple-choice questions in biology, physics, and chemistry used to measure…
- GPQAv9GPQA (Graduate-Level Google-Proof Q&A) is a benchmark of expert-written, four-option multiple-choice questions in biology, physics, and chemistry.
- GANv8GAN stands for generative adversarial network, a class of deep learning generative models in which two neural networks are trained against each other: a generator that fabricates synthetic data and a…
- Fully Connected Layerv7A fully connected layer (also called a dense layer or linear layer) is a layer in an artificial neural network in which every input value connects to every output value through a learned weight.
- Full Softmaxv8Full softmax (also called the standard softmax or exact softmax) is the softmax computation that calculates a probability for every possible output class in a classification model
- Frontier Modelsv11Frontier models are artificial intelligence models at or near a selected boundary of capability, scale, or risk.
- FrontierMathv10FrontierMath is an advanced mathematical reasoning benchmark created by Epoch AI in collaboration with over 60 expert mathematicians, including Fields Medalists Terence Tao, Timothy Gowers, and Richard…
- Fox (benchmark)v9Fox is an evaluation suite for fine-grained, multi-page document understanding by large vision-language models.
- Foundation Modelsv10A foundation model is a machine learning model trained on broad data, generally with self-supervision at scale, that can be adapted to a wide range of downstream tasks.
- Forget Gatev6The forget gate is a sigmoid layer inside a Long Short-Term Memory (LSTM) recurrent neural network that decides, element by element, how much of the previous cell state to keep and how much to discard at each…
- Food ChatGPT Pluginsv5Food ChatGPT Plugins were the subset of third-party plugins published in the ChatGPT plugins store between March 2023 and April 2024 that focused on cooking, recipes, grocery shopping, restaurant discovery…
- AI in the food industryv4AI in the food industry refers to the application of artificial intelligence, machine learning, computer vision, and robotics across the food and beverage value chain, from farming and processing through…
- Fine-tuningv11Fine-tuning is the process of adapting a pretrained machine-learning model by continuing to optimize some or all of its parameters on data selected for a target task, domain, behavior, or population.
- Fine-tune ChatGPT with Perplexity, Burstiness, Professionalism, Randomness and Sentimentality Guidev5The perplexity, burstiness, professionalism, randomness, and sentimentality guide is a prompt engineering pattern that asks ChatGPT to write according to five style sliders, each rated 1 to 10, so a user can…
- Finance ChatGPT Pluginsv5Finance ChatGPT Plugins are a now-deprecated category of third-party extensions that, during 2023 and 2024, connected ChatGPT to live market data, regulatory feeds, payments rails, and personal finance tools.
- Financev8Artificial intelligence in finance is the use of machine learning, deep learning, and generative AI across banking, capital markets, insurance, fintech, and personal finance, where it powers credit scoring…
- Fill-Mask Modelsv6Fill-mask models are language models trained with a masked language modeling (MLM) objective, in which a fraction of the tokens in an input sequence are hidden behind a special [MASK] symbol and the model…
- Figure AIv19Figure AI is a privately held American robotics company that develops electrically powered humanoid robots and the software used to control them. Brett Adcock founded the company in 2022.
- Few-Shot Learningv10Few-shot learning is a branch of machine learning in which a model learns to recognize new classes or perform new tasks from only a very small number of labeled examples, typically one to five per class.
- Feedforward Neural Network (FFN)v13A feedforward neural network (FFN), also called a multilayer perceptron (MLP) when it has multiple layers, is a type of artificial neural network in which information flows in one direction only, from the…
- Feedback Loopv6A feedback loop in machine learning is a cycle in which a deployed model's predictions influence the real world, and the resulting data is then collected and used to retrain the same model
- Federated Learningv10Federated learning is a machine learning technique that trains a shared model across many decentralized devices or servers without moving their raw data to a central location.
- Feature Vectorv10A feature vector is an n-dimensional, ordered list of numerical values that represents the measurable properties of an object, data point, or observation in a format suitable for processing by machine learning…
- Feature specv7A feature spec (short for feature specification) is a declarative description of the input features used by a machine learning model: the name of each feature, its data type, its shape, whether it is required…
- Feature Setv7A feature set is the complete collection of input variables (features, attributes, or predictors) that a machine learning model uses to learn patterns and make predictions.
- Feature Importancesv7Feature importances are numeric scores that quantify how much each input feature contributes to the predictions of a machine learning model.
- Feature Extractionv7Feature extraction is the process of transforming raw data into a smaller set of derived, informative numerical variables called features that capture the essential structure of the input while discarding…
- Feature Engineeringv9Feature engineering is the process of using domain knowledge to create, transform, and select features from raw data so that machine learning models can learn more effectively.
- Feature Crossv7A feature cross (also called a crossed feature or feature interaction) is a synthetic feature created by combining two or more existing features so that a model can learn their joint effect on a prediction.
- Feature Extraction Modelsv5Feature extraction models are machine learning systems that transform raw inputs such as text, images, or audio into dense numerical vectors known as embeddings or hidden-state representations.
- Featurev9In machine learning and statistics, a feature is an individual measurable property or characteristic of a phenomenon being observed, used as an input variable from which a model learns patterns and makes…
- Fashion ChatGPT Pluginsv5Fashion ChatGPT Plugins were a small historical category of third-party plugins that connected ChatGPT to clothing, styling, and apparel services during the 2023 to 2024 plugin era run by OpenAI.
- Fashionv6AI in fashion refers to the use of artificial intelligence, machine learning, and computer vision across the apparel, footwear, and accessories industry.
- False Positive Rate (FPR)v6The false positive rate (FPR) is the proportion of actual negative cases that a test, model, or decision process incorrectly classifies as positive, defined as FPR = FP / (FP + TN) where FP is the number of…
- False positivev9A false positive (FP), also called a Type I error or a false alarm, is an instance whose true label is negative but whose predicted label is positive: the classifier raises an alarm where none was warranted.
- False Negative Ratev7The false negative rate (FNR), also known as the miss rate, is the proportion of actual positive instances that a model or test incorrectly classifies as negative, computed as FNR = FN / (FN + TP).
- False negativev10A false negative (FN), also called a Type II error or a miss, is an instance whose true label is positive but that a classification model or test predicts as negative: a real positive case that the model fails…
- Fairness Metricv8A fairness metric is a quantitative, mathematical measure used to evaluate whether a machine learning model's predictions or decisions treat different demographic groups equitably.
- Fairness Constraintv7A fairness constraint is an explicit mathematical condition imposed on a machine learning model during training, evaluation, or post-processing that forces its predictions to satisfy a specified group-fairness…
- Factorio Learning Environmentv5The Factorio Learning Environment (FLE) is an open source benchmark and research framework that uses the industrial automation game Factorio to evaluate the long-horizon agentic capabilities of large language…
- Exploding Gradient Problemv13The exploding gradient problem is a training failure in deep neural networks where the gradients of the loss function grow exponentially large as they propagate backward through layers during backpropagation…
- Experimenter's Biasv6Experimenter's bias (also called the observer-expectancy effect, experimenter expectancy effect, or experimenter effect) is a type of cognitive bias in which a researcher's expectations or beliefs about the…
- Experience Replayv8Experience replay is a reinforcement learning technique in which an agent stores its past transitions in a memory called a replay buffer and samples random mini-batches of those stored transitions to train on
- ExcelGPTv9ExcelGPT is a Custom GPT available on the GPT Store that helps users build formulas, write macros, and analyze data inside Microsoft Excel, Google Sheets, and Visual Basic for Applications (VBA).
- Examplev6In machine learning, an example is a single data point that a model trains on or makes a prediction about: in supervised settings it is a pair $(x, y)$ where $x$ is a vector of features and $y$ is a label, and…
- Estimatorv6An estimator is a rule, function, or algorithm that takes observed data and produces a value intended to approximate some unknown quantity, typically a parameter of a probability distribution or a function…
- Equalized Oddsv8Equalized odds is a group fairness criterion in machine learning that requires a classifier's true positive rate (TPR) and false positive rate (FPR) to be equal across all groups defined by a protected…
- Equality of Opportunityv6Equality of opportunity is a group-fairness criterion in machine learning that requires a classifier's true positive rate (TPR) to be equal across all groups defined by a sensitive attribute: qualified…
- Epsilon Greedy Policyv6The epsilon-greedy policy (also written as ε-greedy) is a simple action-selection rule for reinforcement learning and multi-armed bandit problems: with probability 1 - ε the agent picks the action with the…
- Epochv13An epoch in machine learning is one complete pass through the entire training dataset, during which every example is presented to the model exactly once to compute gradients and update parameters before the…
- Episode (Reinforcement Learning)v8An episode in reinforcement learning is one complete sequence of interaction between an agent and its environment, starting from an initial state and ending when a terminal state is reached.
- Environment ChatGPT Pluginsv5Environment ChatGPT Plugins were a small, informal grouping of third party extensions for ChatGPT addressing sustainability, air quality, climate awareness, ecological purchasing, and related green living…
- Environmentv7In reinforcement learning (RL), an environment is the external system that an agent interacts with: it receives the agent's actions, transitions to a new state, and returns an observation together with a…
- Entropyv7Entropy is a quantitative measure of the uncertainty, randomness, or average information content in a probability distribution: for a discrete random variable it equals the average number of yes/no questions…
- Entertainment ChatGPT Pluginsv5Entertainment ChatGPT Plugins were a now-deprecated category of third-party plugins that connected ChatGPT to streaming catalogs, recommendation engines, trivia banks, and audio playback services during the…
- AI in entertainmentv5AI in entertainment refers to the use of artificial intelligence across the film, television, music, video game, animation, and live event industries.
- Ensemblev6Ensemble methods are techniques in machine learning that combine the predictions of multiple models, known as base learners, to produce a single prediction that is typically more accurate and robust than any…
- Encoderv9An encoder in machine learning is a neural network component that transforms input data (text, an image, audio, or code) into a compressed, structured representation, often called a latent representation…
- Employmentv8The use of artificial intelligence in employment covers software and statistical systems that companies deploy to recruit, screen, interview, hire, monitor, evaluate, promote, and dismiss workers.
- Embedding vectorv8An embedding vector is a dense, fixed-length array of real numbers that represents a discrete object (such as a word, sentence, image, audio clip, or graph node) as a point in a continuous vector space.
- Embedding Spacev7An embedding space is a continuous, typically high-dimensional vector space in which data objects (words, sentences, images, users, audio clips, code, or other entities) are represented as dense numerical…
- Embedding Layerv10An embedding layer is a neural network component that acts as a trainable lookup table, mapping discrete integer indices (such as word IDs, user IDs, or category codes) to dense, continuous-valued vectors.
- Education Custom GPTsv5Education Custom GPTs are the Custom GPTs listed in the Education category of OpenAI's GPT Store: custom versions of ChatGPT built for teaching, tutoring, study help, and academic research.
- Education ChatGPT Pluginsv8Education ChatGPT plugins were a category of third-party tools that extended ChatGPT with capabilities aimed at students, teachers, parents, and lifelong learners, and they are now deprecated.
- Educationv6In the AI sense, education refers to the use of artificial intelligence (especially large language models like ChatGPT) to teach, tutor, assess, and assist learning.
- EditGPTv9editGPT is an AI proofreading and editing product that combines a Custom GPT inside the GPT Store with a free browser extension for Google Chrome, Mozilla Firefox, and Microsoft Edge.
- Early Stoppingv8Early stopping is a regularization technique that halts the training of an iterative machine learning model as soon as its performance on a held-out validation set stops improving
- Eager Executionv6Eager execution is an imperative, define-by-run mode of running machine learning framework operations in which each operation is evaluated immediately as it is called and returns a concrete value
- ERQAv4ERQA (Embodied Reasoning Question Answering) is a multimodal benchmark released by Google DeepMind in March 2025 to evaluate the embodied reasoning capabilities of vision-language models (VLMs) on robotics…
- EQ-Bench 3v4EQ-Bench 3 is an artificial intelligence benchmark that measures the emotional intelligence of large language models through challenging multi-turn role-plays and transcript-analysis tasks
- E-Commerce ChatGPT Pluginsv9E-Commerce ChatGPT Plugins were third party shopping integrations published in the ChatGPT plugin store that connected the chatbot to online shopping catalogs, price comparison engines, and merchant…
- E-Commercev11E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the internet.
- Dynamic modelv8A dynamic model in machine learning is a model that is retrained frequently or continuously as new data arrives, so that its parameters track changes in the underlying data distribution over time.
- Dynamicv5In machine learning, dynamic describes a model, a training process, or an inference process that runs frequently or continuously on fresh data, as opposed to one that runs once and stays fixed.
- Dynabenchv4Dynabench is an open-source artificial intelligence benchmarking platform that runs in a web browser and supports human-and-model-in-the-loop dataset creation
- Dropout Regularizationv7Dropout regularization is a regularization technique for neural networks that prevents overfitting by randomly setting a fraction of neuron activations to zero on each training step, forcing the network to…
- Downsamplingv5Downsampling is the process of reducing the number of samples, the spatial resolution, or the number of data instances in a signal, image, or dataset in order to lower computational cost and memory use while…
- Document Question Answering Modelsv6Document question answering models (DocQA, sometimes called DocVQA for document visual question answering) are machine learning systems that take a document image or PDF together with a natural language…
- Divisive Clusteringv5Divisive clustering, also called top-down clustering, is a hierarchical clustering method that begins with all data points in a single cluster and recursively splits that cluster into smaller subclusters.
- DistilGPT2v5DistilGPT2 is an English-language autoregressive language model released by Hugging Face on October 3, 2019.
- Diagram & MindMap GPT: PRO Editionv10Diagram & MindMap GPT: PRO Edition is a Custom GPT for ChatGPT listed in the GPT Store.
- Devicev5In machine learning, a device is the hardware target on which tensor operations are executed: a CPU, an NVIDIA GPU through CUDA, an Apple GPU through Metal Performance Shaders, a Google TPU through XLA, or an…
- Dev toolsv7AI dev tools are the software products, libraries, and platforms that developers use to build, ship, and operate applications powered by artificial intelligence models.
- DesignerGPTv8DesignerGPT is a Custom GPT built on top of ChatGPT that turns a short text prompt into a complete, hosted webpage.
- Design ChatGPT Pluginsv5Design ChatGPT Plugins were third-party extensions inside ChatGPT that helped the chatbot create graphic assets, page layouts, logos, banners, and full websites without leaving the conversation, with named…
- Designv6Design is one of the creative fields most visibly transformed by artificial intelligence.
- Derived labelv5A derived label is a label that has been generated programmatically or inferred from other observable signals, rather than collected from direct human annotation of the variable a model is trying to predict.
- Depthwise separable convolutional neural network (sepCNN)v5A depthwise separable convolutional neural network (often abbreviated sepCNN) is a convolutional neural network that replaces standard convolution layers with depthwise separable convolutions.
- Depthv5In machine learning, depth is the number of sequential processing stages a model applies between its input and its output.
