Artificial intelligence and data

Streaming algorithm

A streaming algorithm computes a function of a long data sequence in one pass, keeping a small summary called a sketch and returning an approximate answer.

Streaming database: a database whose tables are maintained continuously from event streams via registered materialized views, rooted in 1992 Tapestry continuous queries; computes results on write, unlike OLAP stores and batch warehouses.

Streaming Systems

Streaming systems process unbounded data continuously using event time, watermarks, windows, triggers, and exactly-once semantics, as codified in the 2015 Dataflow model and the 2018 O'Reilly book Streaming Systems by Akidau, Chernyak, and Lax.

Striim

Striim (pronounced "stream"), founded 2012 as WebAction by GoldenGate Software alumni including Ali Kutay, is a Palo Alto real-time data integration platform using log-based CDC and TQL streaming SQL, sold as Striim Cloud or self-managed software.

Strimzi

Strimzi is an open-source CNCF incubating project (Sandbox 2019, Incubating 2024), developed by Red Hat in 2017, that runs Apache Kafka clusters on Kubernetes and OpenShift via the operator pattern, managing brokers, topics, users, Connect, and MirrorMaker as custom resources.

String-searching algorithm

A string-searching algorithm, also called string matching or substring search, finds occurrences of a pattern string within a longer text; classic algorithms include Knuth–Morris–Pratt, Boyer–Moore, and Rabin–Karp.

Strong exponential time hypothesis

The strong exponential time hypothesis (SETH) is a conjecture in computational complexity that satisfiability of Boolean CNF formulas cannot be solved substantially faster than exhaustive search.

Structural risk minimization

Structural risk minimization (SRM) is an inductive principle for model selection introduced by Vapnik and Chervonenkis in 1974, balancing empirical error against model capacity to prevent overfitting.

Structural similarity

Structural similarity (SSIM) is an image quality metric that compares luminance, contrast, and structure against a reference image, introduced by Zhou Wang and colleagues in 2004.

Structural similarity index measure

The structural similarity index measure (SSIM) is a full-reference image quality metric, published in 2004, that compares a distorted image against a reference for luminance, contrast, and structure.

Structure from motion

Structure from motion (SfM) is a photogrammetric technique that reconstructs 3D scene geometry and camera positions from overlapping photographs, underpinning low-cost terrain and landform mapping in the earth sciences.

Structure tensor

The structure tensor is a matrix in image processing that summarizes predominant gradient directions and their coherence in a neighborhood, used for edge and corner detection and optical flow.

Structured prediction

Structured prediction, also called structured learning or structured-output learning, is a machine learning approach that predicts structured outputs such as sequences, trees, or graphs, seen in part-of-speech tagging and image segmentation.

StyleGAN

StyleGAN is a generator architecture for generative adversarial networks introduced by Tero Karras and colleagues at NVIDIA in 2019, giving direct control over image features at different scales.

Sub-Nyquist sampling

Sub-Nyquist sampling acquires an analog signal at an average rate below its Nyquist rate and reconstructs it, possible only when the signal has known structure such as sparsity or a multiband spectrum.

Subgradient method

The subgradient method is a first-order optimization algorithm that minimizes nondifferentiable convex functions by repeatedly stepping against a subgradient, and it underlies stochastic gradient methods in machine learning.

Subject-specific databases

Subject-specific databases are research data collections organized around one field of inquiry, such as genomics or physics, and cataloged by discipline in registries like re3data, which describes over 3,000 repositories.

Subspace clustering

Subspace clustering is an unsupervised machine learning method that groups data points assumed to lie near a union of low-dimensional subspaces, used in motion segmentation and face clustering.

Substrait

Substrait is an open, cross-language specification (Protobuf-based, Apache-2.0) for exchanging relational-algebra query plans between data engines, distinct from Apache Arrow (data format) and Calcite (internal IR), with SDKs and IBM-run compliance testing.

Subtractive clustering

Subtractive clustering is a fast, one-pass, density-based fuzzy clustering algorithm that estimates the number of clusters and their centers directly from data, reported by Stephen L. Chiu in 1994.

Subword regularization

Subword regularization is a training technique for neural language models that tokenizes each training sentence with a randomly sampled subword segmentation, introduced by Taku Kudo in 2018.

Suffix array

A suffix array is an array of integers giving the starting positions of a text's suffixes in sorted order, enabling fast full-text search through binary search.

Suitability analysis

Suitability analysis, also called land suitability analysis, is a GIS method that rates and maps how suitable land areas are for uses like cropping or urban development.

Sumo Logic

Sumo Logic is a proprietary, SaaS-only log analytics and observability platform that collects, indexes, and analyzes logs, metrics, and telemetry for engineering and security teams.

Super-resolution generative adversarial network

The super-resolution generative adversarial network (SRGAN) is a machine learning method that reconstructs photo-realistic high-resolution images from low-resolution inputs, introduced by Christian Ledig and colleagues in 2016.

Super-resolution mapping

Super-resolution mapping, also called subpixel mapping, is a remote sensing technique that divides each coarse pixel into subpixels, producing hard classified land-cover maps finer than the input imagery.

Super-resolution network

A super-resolution network is a deep neural network that reconstructs a high-resolution image from one or more low-resolution observations by learning the mapping between them from training data.

SuperAnnotate

SuperAnnotate (SuperAnnotate AI, Inc.) is a San Francisco AI data platform company founded in 2018 by brothers Tigran and Vahan Petrosyan, offering multimodal data annotation, evaluation, RLHF workflows, and a managed expert workforce; backed by NVIDIA, Socium Ventures, Base10, Point Nine, and Dell Technologies Capital.

Superintelligence

Superintelligence is a hypothetical general intelligence vastly outperforming the best human brains in every cognitive domain, a concept central to AI risk debates since Bostrom's 2014 book.