Glossary
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A
- Active LearningA special case of machine learning in which a learning algorithm can interactively query a user to obtain the desired outputs at new data points.AI & Machine Learning
- Agentic WorkflowsAutonomous systems where AI agents iteratively plan, execute, and evaluate multi-step tasks using integrated tools and environmental feedback.Core Concepts
- AI AlignmentThe process of ensuring that artificial intelligence systems are aligned with human values and the specific strategic goals of the enterprise.Security & Operations
- Air-Gapped EnvironmentA secure network that is physically isolated from unsecured networks, including the public Internet.Security & Operations
- API GatewayA server that acts as an API front-end, receiving API requests, enforcing throttling and security policies, and routing them to the back-end.Security & Operations
- API IntegrationThe connection between two or more applications, via their APIs, that lets those systems exchange data.Core Concepts
C
- Change Data CaptureA set of software design patterns used to determine and track the data that has changed so that action can be taken using the changed data.Data Architecture
- CI/CDThe automated pipeline for integrating code changes, testing them, and deploying them to production environments continuously and securely.Security & Operations
- Cloud ComputingThe delivery of computing services, including servers, storage, databases, networking, software, analytics, and intelligence, over the Internet.Security & Operations
- Compute GravityThe architectural principle that applications and processing power tend to move closer to where large data sets reside.AI & Machine Learning
- Compute SovereigntyComplete organizational ownership, control, and jurisdictional authority over processing infrastructure and workloads.Core Concepts
- Computer VisionA field of artificial intelligence that trains computers to interpret and understand the visual world.AI & Machine Learning
- Confidential ComputingHardware-based protection of data while it is being processed, using trusted execution environments that isolate computation from the host system.Security & Operations
- Context WindowThe maximum amount of text (measured in tokens) that an LLM can read and reason over in a single query.Core Concepts
- Control BoundariesEnforced technical perimeters that protect sensitive data, workflows, identity, and compliance, built into infrastructure rather than bolted on as policy.Core Concepts
- Control GravityZynolabs' term for the pull that enterprise policies, standards, ownership, and observability must exert across every layer of a system.Core Concepts
D
- Data AnonymizationThe process of removing personally identifiable information from data sets, so that the people whom the data describe remain anonymous.Security & Operations
- Data DriftThe variation in the statistical properties of the target variable, or the input data, over time.AI & Machine Learning
- Data ExfiltrationThe unauthorized, covert transfer of sensitive data from a secure corporate computer or network.Security & Operations
- Data GovernanceThe overall management of the availability, usability, integrity, and security of data employed in an enterprise.Data Architecture
- Data GravityThe phenomenon in which large datasets attract applications, services, and computing power to locate near them because of network latency.Data Architecture
- Data LakeA centralized repository that stores structured and unstructured data in raw form, without requiring a schema up front.Data Architecture
- Data Lake ArchitectureThe structural design and organization of a data lake, including its storage, processing, and management layers.Data Architecture
- Data LakehouseAn open data management architecture that combines the flexibility of data lakes with the management features of data warehouses.Data Architecture
- Data LineageThe lifecycle of data, tracking its origin, transformations, and movement over time across the enterprise.Data Architecture
- Data MeshA decentralized data architecture that organizes data by a specific business domain, providing more ownership to the producers of a given dataset.Data Architecture
- Data MobilizationThe process of making siloed enterprise data accessible, structured, and usable for AI and analytics.Data Architecture
- Data PipelineA set of data processing elements connected in series, where the output of one element is the input of the next one.Data Architecture
- Data SiloA repository of fixed data that remains under the control of one department and is isolated from the rest of the organization.Data Architecture
- Data SovereigntyThe legal and regulatory concept that digital data is subject to the laws of the nation in which it is physically located.Data Architecture
- Data WarehouseA central repository of integrated data from one or more disparate sources, used for reporting and data analysis.Data Architecture
- Deep LearningA subset of machine learning based on artificial neural networks with multiple layers, allowing it to extract higher-level features from raw input.AI & Machine Learning
- DevSecOpsAn approach to culture, automation, and platform design that integrates security as a shared responsibility throughout the entire IT lifecycle.Security & Operations
- Differential PrivacyA mathematical framework for guaranteeing that the output of an algorithm reveals little about any individual data point in the training set.Security & Operations
- Digital TransformationThe integration of digital technology across all areas of a business, changing how it operates.Core Concepts
- Disaster RecoveryPolicies, tools, and procedures for recovering technology infrastructure and systems after a natural or human-induced disaster.Security & Operations
E
- Edge AIThe deployment of artificial intelligence applications in devices throughout the physical world.Data Architecture
- Edge ComputingA distributed computing model that brings computation and storage closer to where data is generated, cutting latency and saving bandwidth.Data Architecture
- Enterprise ArchitectureThe conceptual blueprint that defines the structure and operation of an organization, integrating IT with business goals.Core Concepts
- Event-Driven ArchitectureA software architecture built around the production, detection, and consumption of, and reaction to, state changes (events).Data Architecture
- Explainable AIMethods and techniques in the application of artificial intelligence such that the results of the solution can be understood by humans.Security & Operations
F
- Federated LearningA machine learning approach where a model is trained across multiple decentralized edge devices or servers holding local data samples, without exchanging them.AI & Machine Learning
- Few-Shot LearningThe practice of feeding a machine learning model a small amount of training data to adapt it to a specific task.AI & Machine Learning
- Fine-TuningThe process of taking a pre-trained foundation model and training it further on a specific, proprietary dataset.AI & Machine Learning
- FinOpsThe practice of bringing financial accountability to the variable spend model of cloud computing and AI infrastructure.Security & Operations
- Foundation ModelA large machine learning model trained on broad, diverse data, which can be adapted to a wide range of downstream tasks.Core Concepts
G
- Generative Adversarial NetworkA class of machine learning frameworks where two neural networks contest with each other in a game to generate new, synthetic instances of data.AI & Machine Learning
- Generative AIAI that creates original content, such as text, images, video, audio, or code, in response to a user's prompt.Core Concepts
- GPU VirtualizationTechnology that enables a single physical GPU to be partitioned and shared across multiple virtual machines or containerized workloads simultaneously.Data Architecture
- Graph DatabaseA database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data.Data Architecture
- Graph Neural NetworkA class of deep learning methods designed to perform inference on data described by graphs.AI & Machine Learning
H
- HallucinationA phenomenon in which an AI model generates plausible-sounding but factually incorrect or nonsensical information.Core Concepts
- High AvailabilityA characteristic of a system that aims to ensure an agreed level of operational performance, usually uptime, for a higher than normal period.Security & Operations
- Homomorphic EncryptionA form of encryption that permits computation directly on ciphertext, producing an encrypted result matching operations run on the plaintext.Security & Operations
- Human Approval BoundariesExplicit gates built into automated workflows marking where automation stops and a person decides, preserving human accountability in AI operations.Core Concepts
- Hyperparameter TuningThe process of determining the right combination of hyperparameters that allows the machine learning model to maximize its performance.AI & Machine Learning
I
- Inference EngineThe component of the system that applies logical rules or neural network weights to the knowledge base or input data to deduce new information.Security & Operations
- Infrastructure as CodeManaging and provisioning infrastructure through machine-readable definition files, rather than manual hardware configuration.Security & Operations
K
- Knowledge GraphA network of real-world entities and their relationships, representing facts and semantic meaning in a structured, graph-based format.Core Concepts
- KubernetesAn open-source container orchestration system for automating software deployment, scaling, and management.Security & Operations
L
- Large Language Model LLMA deep learning algorithm that can recognize, summarize, translate, predict, and generate human language.AI & Machine Learning
- Load BalancingThe process of distributing a set of tasks over a set of resources, with the aim of making their overall processing more efficient.Security & Operations
M
- Machine LearningA branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.Core Concepts
- Managed AI OperationsThe ongoing stewardship of a deployed private AI system: operation, governance, evaluation, and tuning that keep it accurate, safe, and auditable.Core Concepts
- MicroservicesAn architectural style that structures an application as a collection of loosely coupled, independently deployable services.Data Architecture
- MLOps Machine Learning OperationsMachine Learning Operations: The set of practices that aims to deploy and maintain machine learning models in production reliably.AI & Machine Learning
- Model DriftThe gradual degradation of a machine learning model’s accuracy and predictive power over time as real-world data changes.AI & Machine Learning
- Model InferenceThe live phase where a trained AI model processes new, unseen data to make predictions or generate outputs.AI & Machine Learning
- Model Inversion AttackAn attack where adversaries reconstruct a model's private training data by exploiting its confidence scores and outputs.Security & Operations
- Model QuantizationThe process of reducing the precision of a model's weights (e.g., from 32-bit floats to 8-bit integers) to shrink its memory footprint and accelerate inference.AI & Machine Learning
- Model RegistryA central repository for managing the lifecycle of machine learning models, including their versions, artifacts, and metadata.Security & Operations
- Multi-Modal AIAI systems that process and synthesize multiple data types, such as text, images, audio, and video, simultaneously.AI & Machine Learning
N
- Natural Language ProcessingA subfield of linguistics, computer science, and AI concerned with the interactions between computers and human language.Core Concepts
- Natural Language UnderstandingA subtopic of natural language processing in artificial intelligence that deals with machine reading comprehension.AI & Machine Learning
- Neural NetworkA series of algorithms that tries to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.Core Concepts
O
P
- Parameter-Efficient Fine-TuningTechniques like LoRA that adapt large pre-trained language models to specific tasks by updating only a small subset of the model's parameters.AI & Machine Learning
- Path to OwnershipZynolabs' four-stage engagement that moves an enterprise from renting AI to owning it: Snapshot, Architecture, Buildout, and Managed AI Operations.Core Concepts
- Private AIArtificial Intelligence systems deployed within secure, fully controlled environments to maintain data sovereignty.Core Concepts
- Prompt EngineeringThe practice of designing and refining inputs (prompts) to get the desired responses from large language models.Core Concepts
- Prompt InjectionA cybersecurity vulnerability where an attacker manipulates an LLM's inputs to bypass its safety guardrails and execute unauthorized commands.Security & Operations
R
- Reinforcement LearningAn area of machine learning concerned with how intelligent agents ought to take actions in an environment to maximize cumulative reward.AI & Machine Learning
- Retrieval-Augmented Generation RAGAn AI framework that improves model responses by dynamically fetching verified data from external, proprietary databases.Data Architecture
- Role-Based Access Control RBACA method of restricting network access based on the designated roles of individual users within an enterprise.Security & Operations
S
- SecOpsA methodology that integrates security protocols directly into standard IT and operational workflows.Security & Operations
- Secure Enterprise BoundariesThe architectural perimeter within which private AI runs: ownership, access, identity, evidence, and control designed as one structure.Core Concepts
- Self-AttentionA mechanism that relates different positions of a single sequence to compute a representation of the sequence.AI & Machine Learning
- Semantic CachingAn optimization technique that caches LLM responses based on the semantic meaning of the prompt rather than exact string matching.Data Architecture
- Semantic SearchA search technique that uses NLP to understand the intent and contextual meaning of a query, rather than matching exact keywords.AI & Machine Learning
- Service MeshA dedicated infrastructure layer that handles service-to-service communication between microservices, using a proxy.Security & Operations
- Shadow ITInformation technology systems built and used within organizations without explicit organizational approval.Core Concepts
- Sovereign AIAI capability an organization or nation controls from start to finish: infrastructure, models, data, and operations, independent of external providers' terms.Core Concepts
- Supervised LearningA machine learning approach defined by its use of labeled datasets to train algorithms that classify data or predict outcomes accurately.AI & Machine Learning
- Synthetic DataArtificially generated data that mimics the statistical properties of real-world data without containing any actual, sensitive information.Core Concepts
T
- Technical DragThe compounding operational friction and cost incurred by maintaining outdated systems or rushed, poorly architected solutions.Core Concepts
- Tensor Processing UnitAn AI accelerator application-specific integrated circuit developed specifically for neural network machine learning.Data Architecture
- TokenizationThe process of breaking down raw text into smaller discrete sub-word units (tokens) that a machine learning model can mathematically process.AI & Machine Learning
- Transfer LearningA research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.AI & Machine Learning
- Transformer ArchitectureA deep learning architecture based on the self-attention mechanism, which weighs the significance of each part of the input data differently.AI & Machine Learning
- Triple Horizon ArchitectureZynolabs’ proprietary framework for structuring digital transformation across Business, Operations, and Infrastructure horizons.Core Concepts
U
V
- Vector DatabaseA specialized database designed to store and query high-dimensional vector embeddings, used for AI search and memory.Data Architecture
- Vendor Lock-InThe condition where switching away from a technology provider becomes prohibitively expensive because data, workflows, and pricing sit under the vendor's control.Core Concepts