NAiOS IconNAiOS Logo
Glosario abierto de IA

NAiOS Wiki

Diccionario divulgativo de la terminología de la IA —conceptos, técnicas, arquitecturas y tendencias— explicado claro y al día. 69 términos.

Glosario educativo e independiente. Algunos términos los implementa NAiOS; otros —como riesgos o malas prácticas (prompt injection, deepfakes)— se recogen solo para entenderlos, no como funciones de la plataforma.

TérminoDefinición
AGI (Artificial General Intelligence)Artificial General Intelligence, capable of any human intellectual task
AI AgentsSystems that execute multi-step tasks without constant supervision
AI AlignmentAligning AI goals with human values
AI Brain FryAcute cognitive fatigue from excessive use or supervision of AI tools. Term coined by researchers from BCG and the University of California (Riverside) in 2026.
AI CopilotAI Assistant integrated into work tools
AI GovernanceRegulatory and management framework for the responsible use of AI
AI OverviewAI-generated summaries in search results
AI PsychosisInformal term (not a recognized clinical diagnosis) for psychotic-like symptoms—delusions, paranoia—associated with the intensive use of AI chatbots.
AI SafetyDiscipline focused on ensuring that AI is safe
AI WrapperApplication that simply wraps an existing model without adding real value
Agentic AIAI capable of planning, deciding, and acting autonomously
Agentic WorkflowsWorkflows where AI agents act autonomously
Algorithmic BiasWhen AI reproduces or amplifies biases present in the data
Chain of Thought (CoT)Technique where AI thinks step-by-step before responding
Context WindowAmount of text a model can remember in a conversation
Data ContaminationWhen evaluation data leaks into training, biasing benchmarks
Data MoatCompetitive advantage of a company thanks to its unique data
Decision IntelligenceUsing AI to improve business decision-making
DeepfakeHyper-realistic AI-generated fake content
Edge AIRun AI directly on the device, without relying on the cloud
EmbeddingsNumerical representation of the meaning of texts or images
Fine-TuningRetraining a model with specific data for a use case
Frontier ModelsThe most advanced and powerful models at all times
GEO (Generative Engine Optimization)The new SEO, optimizing content to be cited by generative AI
Generative AIArtificial intelligence that creates new content (text, image, video, audio)
GroundingGrounding AI responses in real and verifiable data
GuardrailsRestrictions and limits imposed on AI to prevent harm
HallucinationWhen AI generates false information with total confidence
HarnessFramework for testing and evaluating agent performance
Inference Time ComputeDedicate more compute capacity during the response, not training
JailbreakingTechniques for evading model security restrictions
LLM (Large Language Model)Large language model, the foundation of today's chatbots
LoRA / QLoRATechniques for adapting models with limited resources
Local InferenceRunning AI models on your own hardware
Loop EngineeringDesigning the autonomous loops that guide code agents (2026 term)
Mixture of Experts (MoE)Architecture that activates only parts of the model based on the task
Model Context Protocol (MCP)Standard protocol for models to connect with external tools
Model DistillationCompressing a large model into a small one while preserving quality
Model WelfareEthical debate on whether advanced models deserve some form of consideration
ModelOpsOperational management of the AI model lifecycle
Multi-Agent OrchestrationCoordinate multiple AI agents to solve complex tasks together
MultimodalModels that understand and generate text, image, audio and video
NPU (Neural Processing Unit)A chip specialized in accelerating neural network inference with maximum energy efficiency
No-Code AIAI tools that require no programming to use
Prompt DriftWhen a prompt that worked stops delivering good results over time
Prompt EngineeringDesign and optimization of prompts for better AI results
Prompt InjectionAttacks that manipulate AI by inserting malicious instructions
RAG (Retrieval Augmented Generation)Combine real data search with text generation
RLHFReinforcement Learning from Human Feedback
Reasoning ModelsModels designed specifically to reason, not just predict text
Red TeamingTesting an AI by attempting to break it to find vulnerabilities
ScaffoldThe code structure that connects and orchestrates an AI agent
Shadow AIUnauthorized use of AI tools within organizations
Small Language Models (SLM)Lightweight language models, designed to run on devices
Sovereign AIStrategic priority for countries to have their own AI infrastructures
SuperintelligenceAI that surpasses human intellectual capacity in all fields
Synthetic DataArtificially generated data for training models
Synthetic MediaMedia (image, audio, video) artificially created by AI
TOPS (Tera Operations Per Second)Unit that measures the raw performance of an AI accelerator: trillions of operations per second
TemperatureParameter that controls AI creativity vs. precision
Text-to-VideoGenerate video from a text description
The Great IntegrationInformative label for the phase of mass and cross-sector AI adoption across all industries. It is not an academic term or a quote from MIT.
TokenizationProcess of dividing text into units (tokens) that the model can process
TokenmaxxingMaximizing a model's context window. Colloquially, also: using many tokens as a (debatable) productivity metric.
TransformerThe base architecture of almost all current language models
Vibe CodingProgram by describing what you want and letting the AI write the code
Voice CloningClone a human voice with AI from a few seconds of audio
World ModelsModels that learn the dynamics of an environment, not just text
Zero-ShotAbility of a model to perform tasks without being specifically trained