Thursday, July 23, 2026
- Widthv4See also: Machine learning terms Width refers to the number of neurons in a specific layer of a neural network. In modern transformer language models, the...
- WebGPT🤖v9--- Information WebGPT🤖 Platform GPT Store Model Programming Description plugin.wegpt.ai OpenAI URL 8,000 Actions Yes Code Interpreter ...
- WebDev Arenav3Web Development Arena Abbreviation A live, community-driven leaderboard that ranks large language models on their ability to build interactive web...
- Wide Modelv5See also: Machine learning, Deep learning, Recommendation system A wide model is a type of machine learning model that uses a large number of input features,...
- Word Embeddingv8A word embedding is a learned representation of text in which words are mapped to dense vectors of real numbers in a continuous vector space, so that words...
- Whisperv13Whisper is an open-source family of automatic speech recognition (ASR) models developed by OpenAI and first released on September 21, 2022.[^1] Built on an...
- Web Developmentv5See also: Web Development ChatGPT Plugins AI in web development is the use of large language models and related generative systems to design, build, deploy,...
- Writingv6AI is used for writing by applying large language models to draft, edit, rewrite, summarize, and translate text, usually through a chatbot like ChatGPT or...
- Weighted Sumv7A weighted sum is a mathematical operation that combines multiple input values by multiplying each value by a corresponding weight (coefficient) and then...
- Voice Activity Detection Modelsv6See also: Audio Models and Tasks Voice activity detection (VAD), also called speech activity detection (SAD), is the task of deciding which segments of an...
- Weightv6In machine learning and neural networks, a weight is a learnable numerical parameter that determines the strength of the connection between two neurons....
- Wisdom of the Crowdv5Wisdom of the crowd is the observation that the aggregate judgment of a large group of individuals often produces more accurate estimates or decisions than any...
- WORDLY - WORD Gamev8--- Information WORDLY - WORD Game Internal name ChatGPT Model Gaming Description June 19 or 20, 2023 (per third party plugin trackers) ...
- WeirdMLv3--- Full name Benchmark testing whether large language models can do real ML engineering on small, unusual datasets by writing PyTorch code, getting...
- Vibe codingv8Vibe coding is a software development practice in which a programmer describes their intent in plain natural language and relies on a large language model...
- Unsupervised Machine Learningv7See also: Machine learning terms and Unsupervised learning Unsupervised machine learning is a type of machine learning that finds patterns, structures, and...
- Visual Question Answering Modelsv6See also: Vision Language Model and Multimodal Model Visual question answering models are AI systems that take an image and a natural language question about...
- Videosv4See also: Guides This page collects influential video content about artificial intelligence, machine learning, and deep learning. The first section surveys the...
- Validationv4See also: Machine learning terms Validation in machine learning is the process of checking how well a trained model performs on data it did not see during...
- User matrixv7See also: Machine learning terms In collaborative filtering and matrix factorization recommender systems, the user matrix (commonly written U or P) is the...
- Vector databasev10See also: AI terms A vector database is a database that stores data as high-dimensional vectors (numerical embeddings produced by a machine learning model) and...
- Vibe Coding Tips and Tricksv4See also: Vibe Coding Vibe coding is the practice of building software by describing what you want in natural language and letting an AI write the code. The...
- Validation lossv4See also: Machine learning terms Validation loss is the value of a model's loss function measured on a held-out validation set, data the model never sees...
- Upweightingv5See also: Machine learning terms Upweighting is the practice of assigning a larger weight to certain training examples (or groups of examples) so they...
- Vimgolfv3Vimgolf Gym Environment Abbreviation OpenAI Gym style customizable environment and benchmark for VimGolf challenges, used to evaluate AI agents and large...
- Video-MMMUv3Video Multi-Modal Multi-disciplinary Understanding Abbreviation A multi-modal benchmark that evaluates how Large Multimodal Models acquire and apply...
- Validation Setv6A validation set (also called a development set or dev set) is a subset of labeled data that is held out from the training set and used to evaluate a model's...
- Video Classification Modelsv5Video classification models are machine learning systems that assign one or more category labels to a video clip, typically describing the human action...
- Vanishing Gradient Problemv9See also: Machine learning terms The vanishing gradient problem is a difficulty in training deep neural networks where the gradients used to update the network...
- Vision language modelv6A vision-language model (VLM) is a class of multimodal artificial intelligence model that jointly processes visual inputs (typically still images, sometimes...
- Video GPT by VEEDv5Video GPT by VEED (also stylized as VideoGPT by VEED) is an artificial intelligence text-to-video tool developed by the London-based online video editing...
- Uplift Modelingv8Uplift modeling (also called incremental modeling, true lift modeling, or net modeling) is a set of machine learning and statistical techniques that predict...
- Vector embeddingsv11See also: AI terms Vector embeddings are dense numerical representations of objects (text, images, audio, video, code, graphs, or any structured data) that map...
- Variable importancesv4See also: Machine learning terms Variable importances, also called feature importances, are scores assigned to each input variable of a predictive model that...
- True positivev8A true positive (TP) is a prediction that is correctly positive: the model predicts the positive class and the true label is also positive.[^1][^3][^17] It is...
- Training-Serving Skewv9Training-serving skew is a difference between a machine learning model's performance during training and its performance during serving (production inference)....
- Training lossv8See also: Loss function, Validation loss, Learning curve In machine learning, training loss is the value of the loss function computed on the training data...
- Undersamplingv6Undersampling is a class imbalance handling technique in machine learning that removes examples from the majority class of a training set so the minority class...
- Universal Speech Modelv6See also: Papers The Universal Speech Model (USM) is a family of large multilingual speech models developed by Google Research that performs automatic speech...
- Unawareness (Fairness Through Unawareness)v4Unawareness to a sensitive attribute, more commonly called fairness through unawareness (FTU), is a machine learning fairness approach that tries to make a...
- Unidirectionalv7See also: Machine learning terms Unidirectional is a property of a sequence model in which the representation or output at each position depends only on inputs...
- Unidirectional language modelv5See also: Machine learning terms A unidirectional language model is a language model that predicts each token using only the tokens that come before it in the...
- Unconditional Image Generation Modelsv5Unconditional image generation models are generative neural networks that learn the marginal distribution p(x) of a set of training images and produce new...
- Universev4Universe was an open-source software platform that OpenAI released on December 5, 2016 for measuring and training an artificial intelligence agent's general...
- Transformersv13> Note: This article is about the neural network architecture introduced in 2017. For the open-source Python library by Hugging Face, see Hugging Face...
- Unlabeled examplev5See also: Machine learning terms An unlabeled example is a data instance that has one or more features but no label, meaning it carries the inputs a model...
- Underfittingv6Underfitting occurs when a machine learning model is too simple to capture the underlying patterns in the data.[1][3] An underfit model performs poorly not...
- Unsupervised learningv6Unsupervised learning is a branch of machine learning in which algorithms identify patterns, structures, and relationships in data without relying on labeled...
- True negativev9A true negative (TN) is a case that a binary classification model correctly predicts as belonging to the negative class: the true label is negative and the...
- Training Setv8See also: Machine learning terms A training set is the portion of a dataset that a machine learning model learns from: the labeled examples a model processes...
- Transfer Learningv10See also: Machine learning terms Transfer learning is a machine learning technique that reuses knowledge a model has gained on one task or domain to improve...
- Trajectory (Reinforcement Learning)v7A trajectory in reinforcement learning is a sequence of states, actions, and rewards that an agent experiences while interacting with an environment. Formally...
- True positive rate (TPR)v5The true positive rate (TPR) is the proportion of actual positive cases that a classifier correctly identifies as positive, computed as TPR = TP / (TP + FN),...
- Unstable Diffusionv4Unstable Diffusion is a Discord community and affiliated commercial platform, operated by the company Equilibrium AI, dedicated to artificial intelligence (AI)...
- Towerv6See also: two-tower model, dual encoder, cross-encoder, contrastive learning, embedding, recommendation system, information retrieval Not to be confused with...
- Test lossv4See also: Machine learning terms Test loss is the value of a loss function computed on a held-out test data set: data that was used neither for training nor...
- Tensor sizev4See also: tensor, shape, tensor rank, dtype The size of a tensor is a description of how big the tensor is, and the term carries two distinct meanings in...
- Text Generation Modelsv6Text generation models are language models trained to produce coherent natural-language text by predicting tokens one at a time, each conditioned on the...
- Threshold (for decision trees)v5In a decision tree, a threshold is the cut point used in an internal node's split test that decides which child subtree a sample is routed to. For a numerical...
- Text2Text Generation Modelsv5Text-to-text (text2text) generation models are a family of neural network systems that frame many natural language processing tasks as a single problem: given...
- Termination conditionv7See also: Machine learning terms A termination condition, also called a stopping criterion, convergence criterion, or halting condition, is a rule that decides...
- Time Series Analysisv10See also: Machine learning terms Time series analysis is the statistical and computational study of data points indexed in chronological order, with the goal...
- Termsv7Terms is the AI Wiki's top-level glossary, a single alphabetical index that defines and links artificial intelligence vocabulary, machine learning concepts,...
- Trainingv6Training in machine learning is the process of fitting a model's parameters to data so that the model can make accurate predictions or generate useful outputs....
- Tf.Examplev5See also: Machine learning terms tf.train.Example (commonly written as tf.Example) is a Protocol Buffers message type that TensorFlow uses as its standard...
- Text-to-Image Modelsv7See also: Multimodal Models and Tasks Text-to-image models are generative artificial intelligence systems that synthesize a new image from a natural-language...
- Tokenv8See also: Machine learning terms, Tokenization, Byte pair encoding A token is the basic unit of text that a language model reads and writes: a word, a subword...
- Token Classification Modelsv5Token classification models are natural language processing systems that assign a discrete label to every token in an input sequence, where a token is...
- Text Classification Modelsv6See also: Natural Language Processing Models and Tasks Text classification models are machine learning systems that assign one or more predefined categorical...
- Test Setv10A test set is a portion of data held back from model development and used only once, after all training and tuning is complete, to give an unbiased estimate of...
- tf.kerasv8tf.keras is the high-level deep learning API built directly into the TensorFlow machine learning framework, and it has been TensorFlow's official and...
- The New Stack and Ops for AI (OpenAI Dev Day 2023)v5The New Stack and Ops for AI Type OpenAI DevDay 2023 Organization OpenAI (YouTube) Presenters A framework for navigating the unique considerations of...
- Timestepv8See also: Machine learning terms A timestep is a discrete unit of time progression in a sequential process. The term shows up in many corners of machine...
- Text-to-Speech Modelsv5Text-to-speech (TTS) models are machine learning systems that convert written text into spoken audio. The modern lineage runs from DeepMind's WaveNet (2016),...
- Table Question Answering Modelsv5Table question answering models (TableQA models) are machine learning systems that answer natural language questions over structured tabular data such as...
- TPU Workerv6A TPU worker is a virtual machine (VM) running Linux that has direct access to one or more Tensor Processing Unit (TPU) chips and executes the actual TPU...
- Tabular modelsv4Tabular models are machine learning systems that learn from data arranged in tables, where each row is a sample and each column is a feature. The defining...
- Targetv6See also: Machine learning terms In supervised learning, the target is the variable that a model learns to predict from input features. It is the answer side...
- Tabular Classification Modelsv6Part of the Tabular Models hub. See also the sibling survey Tabular Regression Models. Tabular classification models are machine learning systems that predict...
- TensorFlowv9TensorFlow is a free, open-source software library for machine learning and numerical computation, developed by the Google Brain team and first released on...
- τ-benchv13τ-bench (Tau-bench), short for Tool-Agent-User Interaction Benchmark, is an AI benchmark that evaluates language agents' ability to complete complex tasks...
- Tabular Regression Modelsv7See also: Tabular Models and Tasks Tabular regression models are machine learning systems that predict a continuous numeric target from a vector of tabular...
- TensorBoardv6See also: Machine learning terms, TensorFlow, Data Visualization TensorBoard is the open-source visualization toolkit for TensorFlow, described by Google as "a...
- Tensor Shapev4A tensor shape is a tuple of integers that describes the number of elements along each dimension (or axis) of a tensor. For a tensor of rank r, the shape is...
- Tau2-benchv3τ²-bench: Evaluating Conversational Agents in a Dual-Control Environment Abbreviation 2025-06-12 (v0.1.0) Latest version arXiv:2506.07982 (2025-06-09) ...
- Technology ChatGPT Pluginsv6See also: ChatGPT Plugins, ChatGPT Plugin Categories and Technology Technology ChatGPT Plugins were the group of third-party extensions in the ChatGPT Plugins...
- Temporal datav4See also: Machine learning terms Temporal data is data where each observation is tagged with a timestamp, so the order in which observations arrive carries...
- Tabular Q-Learningv5Tabular Q-learning is the classic form of Q-learning, a model-free reinforcement learning algorithm that stores the action-value function Q(s, a) explicitly in...
- Tensorv6See also: Machine learning terms In machine learning, a tensor is a multi-dimensional array of numbers that serves as the fundamental data structure for...
- Tensor Rankv6The rank of a tensor, also referred to as its order or degree, is the number of dimensions (axes or indices) needed to describe the tensor. A scalar has rank...
- TensorFlow Playgroundv5See also: Machine learning terms, Neural network, Deep learning TensorFlow Playground (also called the Neural Network Playground, titled Deep playground in its...
- Technologyv7Technology is one of the largest application domains for artificial intelligence, spanning enterprise IT operations, cloud computing, cybersecurity, software...
- Target Networkv6A target network is a separate, slowly updated copy of a neural network used in deep reinforcement learning to compute stable learning targets, decoupling the...
- TensorFlow Servingv8See also: Machine learning terms TensorFlow Serving (often shortened to TF Serving) is Google's open source system for serving machine learning models in...
- TPU Devicev6A TPU device is a Google-designed application-specific integrated circuit (ASIC), the physical Tensor Processing Unit chip and its host hardware, built to...
- Subsamplingv7Subsampling is the practice of drawing a smaller subset from a larger collection of data points, training examples, features, or signal values, in order to cut...
- TPU resourcev5See also: Machine learning terms, Tensor Processing Unit (TPU) A TPU resource is an allocation of Tensor Processing Unit compute, Google's custom machine...
- Tensor Processing Unit (TPU)v8See also: Machine learning terms, GPU, Deep learning, Edge TPU, AI chip A Tensor Processing Unit (TPU) is a custom application-specific integrated circuit...
- Summarization Modelsv5Summarization models are natural language processing systems that condense a source document, set of documents, or dialogue into a shorter version that...
- Structural risk minimization (SRM)v7Structural risk minimization (SRM) is an inductive principle in statistical learning theory for selecting a learned model that simultaneously fits the training...
