AI & EnterpriseGlossary
Understand the terminology behind AI, enterprise software, and data analytics. Clear definitions without the jargon.
Showing 235 of 235 terms
A/B Testing
Experimental method comparing two versions to determine which performs better. Essential for data-driven optimization.
Access Control List (ACL)
A list specifying which users or systems have permission to access specific resources and what operations they can perform.
ACID (Atomicity, Consistency, Isolation, Durability)
Properties guaranteeing reliable database transactions. ACID compliance ensures data integrity even during failures.
Activation Function
A mathematical function applied to neuron outputs to introduce non-linearity. Common examples include ReLU, sigmoid, and tanh.
Agent
An autonomous AI system that can perceive its environment, make decisions, and take actions to achieve specific goals. In Disruptive Rain, agents can handle complex multi-step tasks like research, analysis, and process automation.
Aggregation
Computing summary statistics like sum, average, or count across data sets. Fundamental operation in analytics and reporting.
Agile
Software development methodology emphasizing iterative development, collaboration, and adaptability. Contrasts with waterfall approach.
Alerting
Automated notifications when metrics exceed thresholds or anomalies occur. Enables proactive incident response.
Anomaly Detection
Identifying unusual patterns that don't conform to expected behavior. Critical for fraud detection, system monitoring, and quality control.
API (Application Programming Interface)
A set of protocols and tools that allow different software applications to communicate with each other. APIs enable integration between Disruptive Rain and your existing systems.
API Authentication
Verifying the identity of API clients before granting access. Common methods include API keys, OAuth, and JWT.
API Gateway
Server acting as entry point for API requests, handling routing, authentication, rate limiting, and monitoring. Simplifies API management.
API Key
Unique identifier used to authenticate API requests. Simple but less secure than token-based authentication.
API Versioning
Practice of managing changes to APIs while maintaining backward compatibility. Ensures smooth transitions for API consumers.
Asynchronous Processing
Handling operations in the background without blocking the caller. Improves responsiveness and enables long-running tasks.
Attention Mechanism
A technique that allows models to focus on relevant parts of input when processing information. Attention is crucial for understanding context in long sequences.
Audit Log
A chronological record of system activities that provides evidence of who did what and when. Audit logs are essential for security monitoring, compliance, and incident investigation.
Auto Scaling
Automatically adjusting computing resources based on demand. Optimizes cost while maintaining performance during traffic spikes.
Backpropagation
The algorithm neural networks use to calculate gradients and update weights. Backpropagation enables efficient learning in deep networks.
Backup
Creating copies of data for recovery in case of loss or corruption. Essential part of disaster recovery strategy.
Bandwidth
Maximum rate of data transfer across network connection. Higher bandwidth supports more concurrent users and larger payloads.
Batch Processing
Processing multiple requests together to improve efficiency. Batching amortizes overhead costs but may increase individual request latency.
Batch vs Stream Processing
Batch processes large volumes at scheduled intervals; stream processes data continuously as it arrives. Each suits different use cases.
BLEU Score
A metric for evaluating machine-generated text by comparing it to reference texts. BLEU measures n-gram overlap and is commonly used for translation quality.
Block Storage
Storage dividing data into fixed-size blocks, each with unique identifier. Offers high performance for databases and applications.
Business Continuity
Planning to ensure critical business functions continue during and after disasters or disruptions. Includes disaster recovery and crisis management.
Business Intelligence (BI)
Technologies and practices for collecting, integrating, analyzing, and presenting business data. BI supports data-driven decision making.
Caching
Storing frequently accessed data in fast storage for quick retrieval. Dramatically improves performance and reduces backend load.
Certificate Authority (CA)
Trusted entity that issues digital certificates verifying identity of websites and services. CAs enable secure HTTPS connections.
Chain-of-Thought
Prompting technique where models explain their reasoning step-by-step before giving answers. Improves accuracy on complex reasoning tasks.
Change Management
Structured approach to transitioning organizations from current to desired state. Critical for successful technology adoption.
CI/CD (Continuous Integration/Continuous Deployment)
Practices automating code integration, testing, and deployment. CI/CD enables rapid, reliable software releases.
Circuit Breaker
Design pattern preventing repeated calls to failing services. Circuit breakers fail fast and allow systems to recover.
Classification
Supervised learning task of assigning predefined categories to inputs. Examples include spam detection, image recognition, and disease diagnosis.
Cloud Computing
Delivery of computing services over the internet, including servers, storage, databases, and software. Offers scalability and pay-as-you-go pricing.
Clustering
Unsupervised learning technique that groups similar data points together. Used for customer segmentation, anomaly detection, and pattern discovery.
Cohort Analysis
Analyzing groups of users sharing common characteristics over time. Reveals patterns in user behavior and retention.
Column Store Database
Database storing data by columns rather than rows. Optimized for analytical queries that scan many rows but few columns.
Compliance
Adherence to laws, regulations, and standards governing industry and operations. Non-compliance risks fines and reputation damage.
Computer Vision
AI field focused on enabling machines to interpret and understand visual information from images and videos.
Container
Lightweight, standalone executable package including application code and dependencies. Containers are portable and efficient.
Content Delivery Network (CDN)
Distributed network of servers delivering content to users based on geographic location. CDNs reduce latency and improve performance.
Context Window
The maximum amount of text (measured in tokens) that an AI model can consider at once. Larger context windows allow the AI to reference more information in a single interaction.
Convolutional Neural Network (CNN)
A neural network architecture designed for processing grid-like data such as images. CNNs use convolution operations to detect patterns.
CORS (Cross-Origin Resource Sharing)
Mechanism allowing web applications to make requests to different domains. CORS headers control cross-origin access for security.
Dashboard
A visual display of key metrics and data points that provides at-a-glance understanding of performance. Dashboards help track KPIs and identify trends.
Data Augmentation
Techniques that create modified versions of existing data to increase training dataset size and diversity. Improves model robustness and generalization.
Data Catalog
Inventory of data assets with metadata, making data discoverable and accessible. Catalogs help users find and understand available data.
Data Cleansing
Process of detecting and correcting corrupt, inaccurate, or irrelevant data. Essential step in preparing data for analysis.
Data Governance
Framework ensuring data quality, security, and compliance through policies and procedures. Good governance makes data trustworthy and valuable.
Data Lake
Storage repository holding vast amounts of raw data in native format. Data lakes support diverse analytics on structured and unstructured data.
Data Lineage
Documentation of data's journey from origin through transformations to final destination. Lineage ensures transparency and aids debugging.
Data Mart
Subset of data warehouse focused on specific business function or team. Data marts provide focused access to relevant data.
Data Pipeline
An automated sequence of processes that move and transform data from sources to destinations. Pipelines ensure data flows reliably and consistently through your systems.
Data Quality
Measure of data's fitness for use, including accuracy, completeness, consistency, and timeliness. High-quality data is essential for reliable analytics.
Data Residency
The physical or geographic location where data is stored and processed. Data residency requirements often arise from regulatory compliance (like GDPR) or corporate policy.
Data Retention Policy
Rules defining how long different types of data are kept and when they're deleted. Balances compliance requirements with storage costs.
Data Visualization
Graphical representation of data to communicate insights clearly. Effective visualization makes complex patterns understandable.
Data Warehouse
Centralized repository that stores integrated data from multiple sources for analysis and reporting. Foundation for business intelligence.
DDoS (Distributed Denial of Service)
Cyber attack that overwhelms systems with traffic from multiple sources, making services unavailable. DDoS protection is crucial for availability.
Deep Learning
A subset of machine learning using neural networks with multiple layers to learn hierarchical representations of data. Deep learning powers modern AI applications like image recognition and language understanding.
Denormalization
Adding redundancy to database design to improve read performance. Trade-off between query speed and data integrity.
DevOps
Culture and practices unifying software development and IT operations. Emphasizes automation, collaboration, and continuous delivery.
Digital Transformation
Integration of digital technology into all business areas, fundamentally changing operations and value delivery.
Disaster Recovery
Strategies and procedures for restoring systems and data after catastrophic events. DR ensures business continuity and data protection.
DNS (Domain Name System)
System translating human-readable domain names into IP addresses. DNS is the internet's phone book.
Docker
Platform for developing, shipping, and running applications in containers. Docker simplifies deployment and ensures consistency across environments.
Edge Computing
Processing data near its source rather than in centralized data centers. Reduces latency and bandwidth usage for IoT and real-time applications.
Embedding
A numerical representation of data (like text or images) that captures semantic meaning. Embeddings enable AI to understand similarity, search, and relationships between pieces of content.
Encryption at Rest
Security measure that protects stored data by converting it into an unreadable format. Even if storage is compromised, data remains inaccessible without the decryption key.
Encryption in Transit
Security measure that protects data while it moves between systems, typically using TLS/SSL protocols. This prevents interception during transmission.
Epoch
One complete pass through the entire training dataset. Models typically train for multiple epochs to learn patterns thoroughly.
ETL (Extract, Transform, Load)
A data integration process that extracts data from sources, transforms it into a usable format, and loads it into a destination system. ETL is fundamental to data pipelines.
Event-Driven Architecture
Design pattern where components react to events rather than direct requests. Enables loose coupling and real-time responsiveness.
Failover
Automatically switching to backup systems when primary fails. Critical for high availability and disaster recovery.
Few-Shot Learning
The ability of models to learn from very few examples. LLMs can perform new tasks with just a handful of demonstrations in the prompt.
Fine-Tuning
The process of further training a pre-trained AI model on specific data to improve its performance for particular tasks or domains. Fine-tuning helps customize AI behavior for your specific use case.
Firewall
Network security system that monitors and controls incoming and outgoing traffic based on predetermined security rules. First line of defense against threats.
Function as a Service (FaaS)
Serverless computing allowing code execution in response to events without managing servers. AWS Lambda is a prime example.
Function Calling
The ability of AI models to invoke external tools or APIs based on user requests. Enables AI to perform actions beyond text generation.
GDPR (General Data Protection Regulation)
European Union regulation on data privacy and protection. GDPR requires organizations to protect personal data and respect privacy rights.
Gradient Descent
An optimization algorithm that iteratively adjusts model parameters to minimize error. Foundation of neural network training.
Graph Database
Database optimized for storing and querying relationships between data. Ideal for social networks, recommendation engines, and knowledge graphs.
GraphQL
Query language for APIs enabling clients to request exactly the data they need. Offers flexibility and efficiency over traditional REST.
Grounding
Techniques that anchor AI responses in factual information, reducing hallucinations. This includes citing sources, referencing documents, and verifying claims against known data.
gRPC
High-performance RPC (Remote Procedure Call) framework using HTTP/2 and Protocol Buffers. Ideal for microservices communication.
Hallucination
When an AI generates confident-sounding but factually incorrect information. Disruptive Rain uses multiple techniques including RAG and grounding to minimize hallucinations.
High Availability
System design ensuring services remain operational despite failures. Achieved through redundancy and failover mechanisms.
HIPAA
Health Insurance Portability and Accountability Act regulating protected health information. HIPAA compliance is required for healthcare data handling.
Horizontal Scaling
Adding more machines to handle increased load. Scales out by distributing work across multiple servers.
Hybrid Cloud
Computing environment combining on-premises infrastructure with public cloud services. Offers flexibility and gradual cloud adoption.
Hyperparameter
Configuration settings for machine learning algorithms that aren't learned from data but set before training. Examples include learning rate and batch size.
IaaS (Infrastructure as a Service)
Cloud service providing virtualized computing resources. Examples include AWS EC2, Azure VMs, offering full infrastructure control.
Idempotency
A property where an operation produces the same result regardless of how many times it's executed. Idempotent APIs are safer and more reliable for retry scenarios.
Identity Provider (IdP)
A system that creates, maintains, and manages identity information while providing authentication services. Examples include Okta, Auth0, and Azure AD.
In-Memory Database
Database storing data in RAM for ultra-fast access. Trades durability for speed in applications requiring real-time responses.
Incident Response
Organized approach to addressing and managing security breaches or cyber attacks. Effective incident response minimizes damage and recovery time.
Indexing
Database optimization technique creating data structures for faster queries. Indexes trade storage space for query performance.
Inference
The process of using a trained AI model to make predictions or generate outputs from new inputs. Inference is what happens when you send a message to an AI and receive a response.
Infrastructure as Code (IaC)
Managing infrastructure through code rather than manual processes. IaC enables version control, testing, and automation of infrastructure.
Intrusion Detection System (IDS)
Security tool that monitors network traffic for suspicious activity and policy violations. IDS alerts administrators to potential threats.
Intrusion Prevention System (IPS)
Security tool that monitors traffic and actively blocks detected threats. IPS combines detection with automated prevention.
IP Address
Unique numerical label identifying devices on network. IPv4 and IPv6 are the current versions.
JSON (JavaScript Object Notation)
Lightweight data interchange format that's easy for humans to read and machines to parse. Standard format for web APIs.
JWT (JSON Web Token)
Compact, URL-safe means of representing claims between parties. JWTs are commonly used for authentication and information exchange.
Key Performance Indicator (KPI)
Quantifiable metric measuring performance against objectives. KPIs help track progress and guide decision-making.
Knowledge Distillation
Training a smaller 'student' model to mimic a larger 'teacher' model's behavior. Distillation creates efficient models that retain much of the original's capability.
Kubernetes
Open-source container orchestration platform automating deployment, scaling, and management. Industry standard for container management.
Large Language Model (LLM)
A type of AI model trained on vast amounts of text data that can understand and generate human-like text. LLMs power conversational AI, content generation, and natural language understanding.
Latency
The time delay between sending a request and receiving a response. Low latency is crucial for real-time AI applications and user experience.
Learning Rate
A hyperparameter controlling how much model weights change during training. Proper learning rate is crucial for efficient and stable training.
Load Balancer
Distributes network traffic across multiple servers to ensure reliability and performance. Prevents any single server from becoming overwhelmed.
Logging
Recording system events and activities for debugging and analysis. Logs are essential for troubleshooting and audit trails.
LoRA (Low-Rank Adaptation)
An efficient fine-tuning technique that trains only a small number of additional parameters rather than the entire model. This reduces computational costs while maintaining performance.
Loss Function
A mathematical function measuring the difference between model predictions and actual values. Training aims to minimize the loss function.
LSTM (Long Short-Term Memory)
A type of RNN that can learn long-term dependencies by using memory cells. LSTMs avoid vanishing gradient problems in sequence learning.
Machine Learning
A field of AI focused on building systems that learn from data without explicit programming. ML algorithms identify patterns and make decisions based on examples.
Master Data Management (MDM)
Process creating single, consistent view of critical business data across organization. MDM eliminates data silos and inconsistencies.
Message Queue
Asynchronous communication method where messages are stored in queue until processed. Decouples systems and handles load spikes.
Metadata
Data about data, describing characteristics like structure, format, and lineage. Metadata makes data discoverable and understandable.
Metrics
Quantitative measurements of system behavior over time. Metrics track performance, health, and business indicators.
Microservices
Architectural approach building applications as collection of small, independent services. Each service runs in its own process and communicates via APIs.
Middleware
Software connecting different applications or services, enabling communication and data management. Bridges systems that wouldn't otherwise interoperate.
Minimum Viable Product (MVP)
Version of product with just enough features to satisfy early customers and validate concepts. MVPs enable rapid learning.
Mixture of Experts (MoE)
A model architecture with multiple specialized sub-models (experts) where a gating mechanism routes inputs to relevant experts. MoE enables efficient scaling.
Model Compression
Techniques to reduce model size while maintaining performance, including quantization, pruning, and distillation. Essential for deploying AI on resource-constrained devices.
Model Quantization
Reducing the precision of model weights to decrease memory usage and increase inference speed. Quantization makes large models more deployable with minimal accuracy loss.
Monitoring
Continuous observation of systems to ensure they're functioning correctly. Monitoring detects issues before they impact users.
Monolith
Traditional application architecture where all components are tightly integrated into single codebase. Simpler but less flexible than microservices.
Multi-Agent System
An AI architecture where multiple specialized agents work together to solve complex problems. Each agent has specific capabilities, and an orchestrator coordinates their collaboration.
Multi-Cloud
Using services from multiple cloud providers. Reduces vendor lock-in and enables best-of-breed solutions.
Multi-Factor Authentication (MFA)
Security method requiring users to provide two or more verification factors to gain access. MFA significantly reduces unauthorized access risk.
Named Entity Recognition (NER)
NLP task of identifying and classifying named entities (people, organizations, locations) in text. Essential for information extraction.
Natural Language Processing (NLP)
AI field focused on understanding, interpreting, and generating human language. NLP powers chatbots, translation, and text analysis.
Network Latency
Time delay in data transmission across network. Low latency is crucial for real-time applications and user experience.
Neural Network
A computational model inspired by biological neural networks, consisting of interconnected layers of nodes (neurons) that process information. Neural networks are the foundation of deep learning.
Normalization
Database design technique organizing data to reduce redundancy. Normalization improves data integrity and reduces storage.
NoSQL Database
Database not using traditional relational tables, optimized for specific data models like documents, graphs, or key-value pairs. Offers flexibility and scalability.
Nucleus Sampling (Top-p)
A sampling method that selects from the smallest set of tokens whose cumulative probability exceeds a threshold p. Provides dynamic vocabulary selection.
OAuth
An open standard for access delegation that allows users to grant third-party applications limited access to their resources without sharing credentials.
Object Storage
Storage architecture managing data as objects rather than files or blocks. Highly scalable for unstructured data. S3 is the prime example.
Observability
Ability to understand system internal state from external outputs. Goes beyond monitoring to enable debugging and optimization.
OLAP (Online Analytical Processing)
Technology for complex analytical queries on multidimensional data. OLAP enables fast analysis of business metrics across dimensions.
OLTP (Online Transaction Processing)
System managing transaction-oriented applications with many concurrent users. OLTP prioritizes data integrity and fast query processing.
Orchestration
The coordination and management of multiple AI agents, services, or processes to accomplish complex tasks. Orchestration determines which agents to engage and how they should collaborate.
Overfitting
When a model learns training data too well, including noise and outliers, resulting in poor generalization to new data. Prevented through regularization and validation.
PaaS (Platform as a Service)
Cloud service providing platform for developing and deploying applications without managing underlying infrastructure. Examples include Heroku, Google App Engine.
Pagination
Splitting large data sets into smaller pages for API responses. Improves performance and user experience.
PCI DSS
Payment Card Industry Data Security Standard for organizations handling credit card data. Ensures secure processing, storage, and transmission of card information.
Penetration Testing
Authorized simulated cyber attack on systems to evaluate security. Pen testing identifies vulnerabilities before malicious actors can exploit them.
Perplexity
A metric measuring how well a language model predicts text. Lower perplexity indicates better prediction—the model is less 'perplexed' by the text.
Pre-training
The initial training phase where a model learns general patterns from large datasets before being fine-tuned for specific tasks. Pre-training creates foundation models.
Predictive Analytics
Using historical data and machine learning to forecast future outcomes. Powers demand forecasting, risk assessment, and trend prediction.
Prescriptive Analytics
Advanced analytics recommending actions to achieve desired outcomes. Goes beyond prediction to suggest optimal decisions.
Principle of Least Privilege
Security practice where users receive only the minimum permissions necessary to perform their job. Reduces security risk and potential damage from compromised accounts.
Prompt Engineering
The practice of crafting effective instructions and context for AI systems to achieve desired outputs. Good prompts improve accuracy, relevance, and consistency of AI responses.
Proof of Concept (POC)
Small-scale implementation testing feasibility of idea or approach. POCs reduce risk before full commitment.
Pub/Sub (Publish/Subscribe)
Messaging pattern where publishers send messages to topics, and subscribers receive them. Enables scalable, decoupled communication.
Public Key Infrastructure (PKI)
Framework for creating, managing, and revoking digital certificates. PKI enables secure authentication and encrypted communications.
Quality Assurance (QA)
Systematic monitoring and evaluation ensuring quality standards are met. QA prevents defects through process and testing.
Query Optimization
Process of selecting the most efficient execution plan for database queries. Reduces response time and resource consumption.
RAG (Retrieval-Augmented Generation)
A technique that enhances AI responses by retrieving relevant information from a knowledge base before generating output. RAG helps AI provide accurate, up-to-date answers grounded in your data.
Rate Limiting
A technique that controls the number of API requests a client can make within a given time period. Rate limiting protects services from overload and ensures fair usage.
RBAC (Role-Based Access Control)
A security approach that restricts system access based on user roles within an organization. RBAC ensures users only access data and features appropriate to their responsibilities.
Real-Time Analytics
The ability to analyze and act on data as it's generated, rather than processing it in batches. Real-time analytics enable immediate insights and faster decision-making.
Recovery Point Objective (RPO)
Maximum acceptable amount of data loss measured in time. RPO determines backup frequency requirements.
Recovery Time Objective (RTO)
Maximum acceptable time to restore service after disruption. RTO guides disaster recovery planning and investment.
Recurrent Neural Network (RNN)
A neural network with connections that form cycles, allowing information to persist. RNNs process sequential data like time series and text.
Redundancy
Duplication of critical components to eliminate single points of failure. Increases reliability and availability.
Refactoring
Restructuring existing code without changing external behavior. Refactoring improves code quality and reduces technical debt.
Regression
Supervised learning task of predicting continuous numerical values. Used for price forecasting, demand prediction, and trend analysis.
Regularization
Techniques that prevent overfitting by penalizing complex models. Common methods include L1/L2 regularization, dropout, and early stopping.
Reinforcement Learning
A learning paradigm where agents learn optimal behaviors through trial and error, receiving rewards or penalties for actions. Used in game AI, robotics, and optimization.
Relational Database
Database organizing data into tables with relationships between them. Uses SQL for querying. Foundation of traditional data management.
ReLU (Rectified Linear Unit)
A popular activation function that outputs the input if positive, otherwise zero. ReLU helps deep networks train efficiently.
Replication
Copying and maintaining database copies across multiple locations. Replication improves availability, performance, and disaster recovery.
REST API
A type of API that uses HTTP requests to access and manipulate data. REST APIs are stateless, scalable, and widely used for web service integration.
Retry Logic
Automatically retrying failed operations with backoff strategies. Essential for handling transient failures and improving reliability.
Return on Investment (ROI)
Measure of profitability comparing gains to costs. ROI justifies technology investments and prioritizes initiatives.
Risk Management
Identifying, assessing, and mitigating risks to minimize negative impacts. Essential for project success and business continuity.
SaaS (Software as a Service)
Cloud-delivered software applications accessed via web browser. Examples include Salesforce, Google Workspace. No installation or maintenance required.
SAML (Security Assertion Markup Language)
An XML-based standard for exchanging authentication and authorization data between identity providers and service providers. SAML enables enterprise SSO integration.
Schema
Blueprint defining structure of data, including tables, fields, and relationships. Schemas organize and constrain data storage.
Scrum
Agile framework organizing work into sprints with defined roles (Product Owner, Scrum Master, Team) and ceremonies.
SDK (Software Development Kit)
A collection of tools, libraries, and documentation that developers use to build applications that integrate with a platform. SDKs simplify development and ensure best practices.
Security Information and Event Management (SIEM)
Platform that collects, analyzes, and correlates security data from multiple sources. SIEM enables threat detection and compliance reporting.
Sentiment Analysis
The process of determining emotional tone or opinion in text. Used for brand monitoring, customer feedback analysis, and social media insights.
Serverless
Cloud computing model where provider manages infrastructure and auto-scales. Developers focus solely on code, paying only for execution time.
Service Level Agreement (SLA)
Contract defining expected service quality, including uptime, performance, and support response times. SLAs set clear expectations.
Service Level Indicator (SLI)
Quantitative measure of service level, such as uptime percentage or response time. SLIs are measured against SLOs.
Service Level Objective (SLO)
Target level for service reliability, often stricter than SLA. SLOs guide internal engineering decisions.
Service Mesh
Infrastructure layer managing service-to-service communication in microservices. Handles routing, security, and observability.
Sharding
Horizontal partitioning of database across multiple machines. Sharding enables databases to scale beyond single server capacity.
SOAP (Simple Object Access Protocol)
Protocol for exchanging structured information using XML. SOAP provides strong typing and built-in error handling.
SOC 2
A compliance framework that evaluates how organizations manage customer data based on five trust principles: security, availability, processing integrity, confidentiality, and privacy.
Sprint
Time-boxed period (typically 1-4 weeks) for completing defined work in Agile methodologies. Enables regular progress and feedback.
SQL (Structured Query Language)
Standard language for managing and querying relational databases. SQL enables data retrieval, insertion, updates, and deletion.
SSO (Single Sign-On)
An authentication method that allows users to access multiple applications with one set of login credentials. SSO simplifies user management and improves security.
Stakeholder
Individual or group with interest in project or organization. Managing stakeholder expectations is crucial for success.
Streaming Data
Continuous flow of data generated in real-time. Requires specialized processing for immediate insights and actions.
Supervised Learning
A machine learning approach where models learn from labeled training data. The algorithm learns to map inputs to outputs based on example input-output pairs.
Synchronous Processing
Processing where the caller waits for operation completion before continuing. Simpler but can cause delays and timeouts.
Synthetic Data
Artificially generated data that mimics real data characteristics. Used for training when real data is scarce, expensive, or privacy-sensitive.
Technical Debt
Implied cost of rework caused by choosing quick solutions over better long-term approaches. Technical debt accumulates and slows development.
Temperature
A parameter controlling randomness in AI text generation. Lower temperatures produce more focused, deterministic outputs; higher temperatures increase creativity and variation.
Terraform
Popular IaC tool for building, changing, and versioning infrastructure. Works across multiple cloud providers.
Test Set
Data completely isolated from training and validation, used for final model evaluation. Provides unbiased assessment of real-world performance.
Throttling
Controlling the rate of requests to prevent overload. Similar to rate limiting but often applied dynamically based on load.
Throughput
The number of requests or operations a system can handle per unit time. High throughput is essential for serving AI to many concurrent users.
Time Series Database
Database optimized for handling time-stamped data. Ideal for metrics, logs, IoT sensor data, and financial data.
TLS/SSL
Cryptographic protocols providing secure communication over networks. TLS (Transport Layer Security) is the successor to SSL (Secure Sockets Layer).
Token
The basic unit of text that AI models process. A token is roughly 4 characters or about 3/4 of a word in English. Token counts affect processing time and costs.
Tokenization
The process of breaking text into smaller units (tokens) that AI models can process. Different tokenization strategies affect model performance and efficiency.
Tool Use
AI systems' capability to interact with external tools, databases, or APIs to accomplish tasks. Extends AI beyond language understanding to practical execution.
Top-k Sampling
A text generation technique that considers only the k most likely next tokens. Top-k sampling balances quality and diversity in generated text.
Total Cost of Ownership (TCO)
Complete cost of technology including acquisition, operation, and maintenance. TCO informs build vs. buy decisions.
Tracing
Following requests as they propagate through distributed systems. Tracing helps identify bottlenecks and failures in complex architectures.
Transaction
A sequence of database operations treated as a single unit. Transactions either complete fully or not at all, ensuring data consistency.
Transfer Learning
A technique where knowledge learned from one task is applied to a related but different task. Transfer learning accelerates training and improves performance with limited data.
Transformer
A neural network architecture that uses attention mechanisms to process sequential data in parallel. Transformers power modern LLMs and enable breakthrough performance in NLP.
Underfitting
When a model is too simple to capture underlying patterns in data, resulting in poor performance on both training and new data.
Unsupervised Learning
Machine learning where algorithms find patterns in unlabeled data without predetermined categories. Common for clustering, anomaly detection, and dimensionality reduction.
User Acceptance Testing (UAT)
Final testing phase where end users validate system meets requirements. UAT approval gates production deployment.
Validation Set
A portion of data held out during training to evaluate model performance and tune hyperparameters. Helps detect overfitting.
Vector Database
A specialized database optimized for storing and querying embedding vectors. Vector databases enable semantic search—finding content by meaning rather than exact keywords.
Vendor Lock-in
Dependency on specific vendor making it difficult to switch to alternatives. Lock-in reduces flexibility and negotiating power.
Vertical Scaling
Increasing capacity of existing machines (more CPU, RAM). Scales up but has hardware limits.
Virtual Machine (VM)
Software emulation of physical computer, running its own operating system. VMs enable resource sharing and isolation.
VPN (Virtual Private Network)
Technology creating secure, encrypted connections over public networks. VPNs protect data in transit and enable secure remote access.
Vulnerability Assessment
Systematic examination of systems to identify security weaknesses. Helps prioritize remediation efforts based on risk.
Webhook
A method for one application to send real-time data to another when specific events occur. Webhooks enable automated workflows and instant notifications.
WebSocket
Protocol providing full-duplex communication channels over a single TCP connection. Enables real-time, bidirectional data flow.
XML (Extensible Markup Language)
Markup language encoding documents in human and machine-readable format. Common in enterprise integrations and SOAP APIs.
Zero Trust
A security model that requires strict identity verification for every person and device trying to access resources, regardless of whether they are inside or outside the network perimeter.
Zero-Shot Learning
Performing tasks without specific training examples, relying solely on instructions. Modern LLMs excel at zero-shot tasks due to their broad pre-training.
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