Thursday, July 23, 2026
- Targetv6In supervised learning, the target is the variable that a model learns to predict from input features.
- 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 through realistic, multi-turn interactions with…
- Tabular Regression Modelsv7Tabular regression models are machine learning systems that predict a continuous numeric target from a vector of tabular features, where rows are samples and columns are heterogeneous attributes (numeric…
- TensorBoardv6TensorBoard is the open-source visualization toolkit for TensorFlow, described by Google as "a suite of visualization tools to understand, debug, and optimize TensorFlow programs for ML experimentation." It…
- Tensor Shapev4A tensor shape is a tuple of integers that describes the number of elements along each dimension (or axis) of a tensor.
- Tau2-benchv3τ²-bench (also written Tau2-bench or τ^2-bench) is a benchmark for evaluating conversational AI agents in dual-control environments, where both the agent and a simulated user can call tools to read from and…
- Technology ChatGPT Pluginsv6Technology ChatGPT Plugins were the group of third-party extensions in the ChatGPT Plugins store that focused on technology news, software documentation, repository search, and general developer or…
- Temporal datav4Temporal data is data where each observation is tagged with a timestamp, so the order in which observations arrive carries meaning.
- 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 a lookup table, the Q-table
- Tensorv6In machine learning, a tensor is a multi-dimensional array of numbers that serves as the fundamental data structure for representing and manipulating data.
- 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.
- TensorFlow Playgroundv5TensorFlow Playground (also called the Neural Network Playground, titled Deep playground in its source repository, and, in Google's education properties, simply Playground) is a free, interactive…
- Technologyv7Technology is one of the largest application domains for artificial intelligence, spanning enterprise IT operations, cloud computing, cybersecurity, software development, networking, semiconductor…
- Target Networkv6A target network is a separate, slowly updated copy of a neural network used in deep reinforcement learning to compute stable learning targets
- TPU Devicev6A TPU device is a Google-designed application-specific integrated circuit (ASIC), the physical Tensor Processing Unit chip and its host hardware
- 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 compute cost, add regularization, or rebalance a…
- TPU resourcev5A TPU resource is an allocation of Tensor Processing Unit compute, Google's custom machine learning accelerator chips, that you reserve and run as a unit
- Summarization Modelsv5Summarization models are natural language processing systems that condense a source document, set of documents, or dialogue into a shorter version that preserves the most important information.
- 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 data and controls the capacity of the hypothesis…
- Supervised Machine Learningv10Supervised machine learning is a branch of machine learning in which a model learns a mapping from inputs to outputs by training on labeled examples, where every input (a feature vector) is paired with the…
- Summaryv4In TensorFlow, a summary is a piece of data written to disk during training so that it can later be visualized in TensorBoard. The tf.summary module is the API used to record those values.
- TPU Typev5The types of TPU (Tensor Processing Unit) are the successive generations of custom machine-learning accelerator that Google has built since 2015: v1, v2, v3, v4, v5e, v5p, v6e (Trillium), and v7 (Ironwood).
- TPU Slicev6A TPU slice is a collection of Tensor Processing Unit (TPU) chips that all sit inside the same Google Cloud TPU Pod and are connected to one another by a high-speed inter-chip interconnect (ICI).
- Synthetic Featurev6A synthetic feature (also called a constructed feature or derived feature) is a variable created by transforming, combining, or otherwise manipulating one or more existing features in a dataset, rather than…
- TPU Chipv9This article covers the TPU chip and its hardware. For the broader topic, see Tensor Processing Unit (TPU).
- TPU Masterv6The TPU master is the control and coordination role in Google's Tensor Processing Unit (TPU) system that drives the actual TPU computation.
- System promptv6A system prompt is a special set of instructions, guidelines, persona definitions, and contextual information given to a large language model (LLM) before any user input
- TPU Podv6A TPU Pod is a single Google supercomputer built from many Tensor Processing Unit (TPU) chips wired directly to each other by a high-speed Inter-Chip Interconnect (ICI) fabric arranged as a 2D or 3D torus, so…
- Stridev7Stride is the step size by which a filter (or pooling window) moves across the input in a convolutional neural network (CNN): a stride of 1 shifts the filter one position at a time and visits every location…
- SimpleBenchv3SimpleBench is a text-only benchmark for large language models created by Philip, the host of the AI Explained YouTube channel, with collaborator Hemang.
- SimpleQAv6SimpleQA is a factuality benchmark released by OpenAI on October 30, 2024 that measures whether large language models can answer short, fact-seeking questions correctly instead of producing hallucinations.
- Social Media ChatGPT Pluginsv4Social Media ChatGPT Plugins were third-party extensions for ChatGPT that connected the chat window to social platforms such as Twitter (rebranded to X in July 2023), LinkedIn, YouTube, Reddit, and various…
- Sigmoid Functionv12The sigmoid function is a mathematical function that maps any real number to a value between 0 and 1 using the formula $$\sigma(x) = \frac{1}{1 + e^{-x}}$$, producing a smooth S-shaped curve.
- Software Development ChatGPT Pluginsv4Software Development ChatGPT Plugins were a now-deprecated category of ChatGPT plugins that connected ChatGPT to the wider software development life cycle, including version control, repository analysis, issue…
- SmolVLAv5SmolVLA (Small Vision-Language-Action) is a compact, open-source vision-language-action model (VLA) for robotics developed by Hugging Face and released in June 2025.
- Stepv5In machine learning, a step is one discrete update in an iterative process, most often a single update of a model's parameters computed from one mini-batch of training data (also called a training step…
- Size invariancev6Size invariance, also called scale invariance, is the property of a model, feature, or algorithm that produces the same output (or class label) regardless of the size at which an object appears in the input.
- Space ChatGPT Pluginsv4Space ChatGPT plugins were a group of third-party tools that extended ChatGPT with the ability to fetch astronomical imagery, track the International Space Station, retrieve Mars rover photographs, query…
- Step sizev6In machine learning, the step size (also called the learning rate, usually written as the Greek letter $$\eta$$ or $$\alpha$$) is the scalar that controls how far the parameters of a model move on each update…
- Similarity Measurev8A similarity measure (also called a similarity function or similarity metric) is a real-valued function that quantifies the degree of resemblance between two objects, returning a large value when the objects…
- Software ChatGPT Pluginsv5Software ChatGPT Plugins were a broad category of third-party extensions inside ChatGPT that connected the chatbot to general purpose software products and software-as-a-service platforms.
- Sparse Representationv7Sparse representation is a data encoding strategy in which most values in a vector, matrix, or tensor are zero (or near zero), with only a small fraction of elements carrying non-zero values.
- Sparse Featurev7A sparse feature is a feature in machine learning whose values are predominantly zero or empty across a dataset.
- Selection Biasv8Selection bias is a systematic error that occurs when the data used for analysis, training, or evaluation does not accurately represent the population or domain it is intended to describe
- Servingv4In machine learning, serving (also called model serving or inference serving) is the process of deploying a trained model into a production environment so it can answer prediction requests, usually exposed as…
- Sentence-transformers/all-mpnet-base-v2 modelv5sentence-transformers/all-mpnet-base-v2
- Sentence-transformers/all-MiniLM-L6-v2 modelv6Sentence-transformers/all-MiniLM-L6-v2 model
- Self-Improvement ChatGPT Pluginsv5Self-Improvement ChatGPT Plugins were third party tools available inside the ChatGPT plugins marketplace that focused on personal growth, habit formation, journaling, decision making, mindfulness, and…
- AI in retail and e-commercev3AI in retail and e-commerce refers to the use of artificial intelligence techniques across the retail value chain, from how products are recommended and searched for to how they are priced, stocked, delivered…
- Sensitive Attributev4A sensitive attribute (also called a protected attribute or protected characteristic) is any feature in a dataset that corresponds to a legally or ethically protected personal trait, such as race, sex or…
- Semi-Supervised Learningv9Semi-supervised learning is a machine learning approach that trains a model on a small amount of labeled data together with a large amount of unlabeled data
- AI in self-improvementv3AI in self-improvement refers to the use of artificial intelligence, and since 2023 especially generative AI built on large language models, in consumer products aimed at personal development.
- Self-trainingv7Self-training is a semi-supervised learning procedure in which a model trained on a small labeled set is used to generate predictions on unlabeled data
- Shrinkagev5Shrinkage in machine learning and statistics is a regularization technique that deliberately pulls model coefficient estimates toward zero, or toward some other fixed shrinkage target
- Shopping ChatGPT Pluginsv4Shopping ChatGPT Plugins were a now-deprecated set of third party tools, published in the ChatGPT plugin store between March 23, 2023 and April 9, 2024, that connected the chatbot to product catalogs, price…
- Sequence-to-Sequence Taskv10A sequence-to-sequence (seq2seq) task is any machine learning problem in which a model receives a variable-length input sequence and produces a variable-length output sequence, where the input and output may…
- Search Engine ChatGPT Pluginsv4Search engine ChatGPT plugins were a class of third party and first party extensions for ChatGPT that gave the chatbot the ability to query the open web, fetch the contents of a specific URL, and return cited…
- Self-Supervised Learningv9Self-supervised learning (SSL) is a machine learning approach in which a model learns representations from unlabeled data by generating its own supervisory signal from the structure of the data itself
- Sentiment Analysisv9Sentiment analysis, also called opinion mining or emotion AI, is the use of natural language processing to automatically determine the sentiment, emotion, or opinion expressed in a piece of text, typically…
- Segment Anything Model and Dataset (SAM and SA-1B)v8Segment Anything Model (SAM) is a promptable image segmentation foundation model released by Meta AI on April 5, 2023 that lets users "cut out" any object in an image with a single click, box, or mask prompt…
- Sequence Modelv8A sequence model is a class of machine learning models that processes, generates, or predicts ordered data where the position and surrounding context of each element carry meaning.
- Sentence Similarity Modelsv5Sentence similarity models are machine learning systems that map natural language sentences to fixed-length numerical vectors (sentence embeddings) so that semantically related sentences sit close together in…
- Shape (Tensor)v4In machine learning, the shape of a tensor is the tuple of integers giving the size of the tensor along each of its axes.
- Science ChatGPT Pluginsv4Science ChatGPT plugins were a group of third-party tools that extended ChatGPT with the ability to perform exact computation, fetch peer-reviewed literature, run symbolic mathematics, retrieve curated…
- Scalingv8In machine learning and artificial intelligence, scaling is an umbrella term for several distinct practices: (1) feature scaling, the data-preprocessing step that rescales input features to a common range so…
- Sampling with replacementv7Sampling with replacement is a method of drawing items from a population in which each selected item is returned to the pool before the next draw, so the same item can be chosen more than once.
- Scalarv9A scalar is a single numerical value, a quantity with magnitude but no direction, and the simplest object in linear algebra and machine learning.
- Runwayml/stable-diffusion-v1-5 modelv7Runwayml/stable-diffusion-v1-5 is the Hugging Face repository name of the Stable Diffusion v1.5 checkpoint, a text-to-image latent diffusion model published on October 20
- Robotics Modelsv4Robotics models are machine learning systems that give robots the ability to perceive their surroundings, plan actions, and execute motor control.
- Rotational invariancev4Rotational invariance is the property of a model, function, or feature whose output does not change when the input is rotated.
- Rootv4In machine learning, the root is the starting node of a decision tree: the single topmost node that holds the entire training set and encodes the first condition the tree evaluates, at depth 0.
- Scoringv4Scoring is the process of applying a trained machine learning model to data so it produces an output number, either a prediction (probability, class score, or ranking value) emitted at inference time, or a…
- SEO ChatGPT Pluginsv4SEO ChatGPT Plugins were a group of third-party extensions for ChatGPT that handled search engine optimization tasks (keyword research, on-page audits, SERP analysis, content briefs, and link-building…
- Saverv4In machine learning, a Saver is a utility or class that persists and restores the state of a model, its variables, and its optimizer to disk, so training can be paused, resumed, evaluated, or deployed without…
- Sampling Biasv7Sampling bias is a systematic error in statistics and machine learning that occurs when a sample is collected so that some members of the intended population have a higher or lower probability of being…
- Search Enginev4A search engine is a software system that retrieves information from a corpus (the web, a private dataset, or a document store) and ranks results by relevance to a user query.
- Root Mean Squared Error (RMSE)v5Root Mean Squared Error (RMSE), also known as root mean square deviation (RMSD), is a regression evaluation metric equal to the square root of the average of the squared differences between predicted and…
- SEOv4Search engine optimization (SEO) is the practice of preparing websites and other content so that search engines surface them in response to user queries.
- SWE-bench Verifiedv7SWE-bench Verified is a 500-problem, human-validated subset of the SWE-bench software engineering benchmark, released on August 13
- Research & Analysisv5Research & Analysis in the AI sense refers to the use of artificial intelligence, especially large language models paired with retrieval-augmented generation, to find information, read sources, summarise…
- Recall (metric)v6Recall is a classification and retrieval metric that measures the proportion of actual positive instances a model correctly identifies, defined as TP / (TP + FN)
- Regularization Ratev9The regularization rate (commonly denoted as $$\lambda$$ or alpha) is a hyperparameter that controls the strength of the penalty applied to a model's parameters during training.
- Reporting Biasv4Reporting bias is a type of data bias in machine learning that occurs when the frequency of events, properties, or outcomes captured in a dataset does not reflect their real-world frequency, because people…
- Rewardv8In reinforcement learning (RL), a reward is a scalar feedback signal that an environment sends to an agent after each action, quantifying how desirable that action's outcome was
- Representationv6A representation in machine learning is the format in which a data example is encoded before a model processes it: the same image can be represented as raw pixels, a list of hand-designed measurements, or a…
- Return (Reinforcement Learning)v7In reinforcement learning, the return (commonly denoted $$G_t$$) is the total cumulative reward an agent receives from time step $$t$$ onward, usually with future rewards discounted by a factor $$\gamma$$.
- Ridge Regularizationv7Ridge regularization, also known as L2 regularization or Tikhonov regularization, is a technique in statistics and machine learning that adds a squared L2-norm penalty to a model's loss function.
- Recommendation Systemv10A recommendation system (also called a recommender system) is an information filtering system that predicts a user's preferences and ranks the items most likely to interest that user, such as the movies…
- Regression (statistics and machine learning)v7Regression is a family of statistical and machine learning methods for modelling the relationship between a numeric outcome variable and one or more explanatory variables (often called predictors, features, or…
- AI and religionv3AI and religion refers to the use of artificial intelligence within religious life and to the responses that faith traditions have given to AI.
- Religion ChatGPT Pluginsv3Religion ChatGPT Plugins were a small topical grouping inside the ChatGPT plugin catalogue that gathered third-party extensions for scripture lookup, hadith retrieval, prayer scheduling, and faith community…
- Reinforcement learningv15Reinforcement learning (RL) is a branch of machine learning in which an agent learns to make decisions by taking actions in an environment to maximize a cumulative reward signal, discovering good behavior…
- Rectified Linear Unit (ReLU)v10The Rectified Linear Unit (ReLU) is the most widely used activation function in deep learning, defined mathematically as $$f(x) = \max(0, x)$$: it returns the input directly when positive and outputs zero…
- Replay Bufferv6A replay buffer (also called an experience replay buffer or replay memory) is a fixed-size memory that stores an off-policy reinforcement learning agent's past transitions, each a tuple of state, action…
- Question Answering Modelsv5Question answering (QA) models are natural language processing systems that take a natural-language question as input and return a natural-language answer, optionally grounded in a supplied passage, document…
- Random Policyv7A random policy is a reinforcement learning policy that chooses actions from a fixed probability distribution, most commonly the uniform distribution, independent of the current state and of any learned value…
- Quantile bucketingv4Quantile bucketing, also called quantile binning, equal-frequency binning, or quantile discretization
- Rank (Tensor)v4In machine learning and deep learning frameworks, the rank of a tensor is the number of dimensions (axes) it has: the count of indices you must supply to pick out a single scalar element.
- Raterv5A rater is a person (or, increasingly, a model) who assigns labels, scores, or judgments to data items so those items can be used to train, evaluate, or align a machine learning system.
- Quantilev4A quantile is a cut point that divides a probability distribution or a sorted dataset into intervals containing equal portions of the probability or the observations.
