Popular
Popular public definitions for this language. If a reviewed translation is missing, Dictionary shows a labeled machine-assisted draft.
Popular public definitions for this language. If a reviewed translation is missing, Dictionary shows a labeled machine-assisted draft.
Borrador de traduccion automatica (Spanish) for "Fine-Tuning Training Checkpoint": Fine-Tuning Training Checkpoint is a ml recovery artifact that saves model state during learning for adaptation of a model to a domain. It uses weights, optimizer state, and run metadata so teams can resume or inspect training safely while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Fine-Tuning Training Checkpoint when the fine-tuning run used curated examples, so the team could resume or inspect training safely before the model moved into evaluation.”
Borrador de traduccion automatica (Spanish) for "CI Approval Step": CI Approval Step is a devops workflow control that requires review before a sensitive change proceeds for continuous integration workflows. It uses role checks, comments, and audit logs so teams can keep high-risk automation accountable while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used CI Approval Step when a pull request entered the build queue, so the team could keep high-risk automation accountable before the deployment window opened.”
Payload Autonomy Stack es una definicion publica de sistemas espaciales para el area Payload. Explica como la capacidad Autonomy Stack ayuda a personas y agentes a reconocer riesgos, coordinar decisiones, citar evidencia y mantener limites operativos seguros y confiables.
“Un equipo uso Payload Autonomy Stack durante trabajo de sistemas espaciales en Payload, para comparar senales, elegir el siguiente paso y documentar la decision sin exponer datos privados.”
Borrador de traduccion automatica (Spanish) for "TLS Resolver Cache": TLS Resolver Cache is a networking performance layer that stores DNS answers for reuse until they expire for encrypted transport setup. It uses TTL rules, cache keys, and invalidation so teams can reduce lookup latency while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The network engineering team used TLS Resolver Cache when a certificate neared expiration, so the team could reduce lookup latency before traffic crossed a service boundary.”
Borrador de traduccion automatica (Spanish) for "Environment Artifact Signature": Environment Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for configuration for a runtime stage. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used Environment Artifact Signature when staging and production drifted, so the team could trust deployed packages before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "CPU Backpressure Control": CPU Backpressure Control is a compute stability pattern that slows incoming work when downstream capacity is limited for general-purpose processor scheduling. It uses queues, retry budgets, and admission control so teams can avoid overload cascades while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The platform engineering team used CPU Backpressure Control when the service hit a compute ceiling, so the team could avoid overload cascades before the workload scaled up.”
Borrador de traduccion automatica (Spanish) for "Edge Checkpoint Restore": Edge Checkpoint Restore is a compute recovery workflow that resumes work from a saved state for globally distributed runtime. It uses snapshots, state files, and integrity checks so teams can recover long-running work while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The platform engineering team used Edge Checkpoint Restore when the request arrived near a user, so the team could recover long-running work before the workload scaled up.”
Evaluation Model Router es una definicion publica de inteligencia artificial para el area Evaluation. Explica como la capacidad Model Router ayuda a personas y agentes a reconocer riesgos, coordinar decisiones, citar evidencia y mantener limites operativos seguros y confiables.
“Un equipo uso Evaluation Model Router durante trabajo de inteligencia artificial en Evaluation, para comparar senales, elegir el siguiente paso y documentar la decision sin exponer datos privados.”
Borrador de traduccion automatica (Spanish) for "Experiment Feature Store": Experiment Feature Store is a ml service that serves consistent features to training and inference for controlled model comparison. It uses versioned feature definitions, freshness checks, and access policies so teams can avoid training-serving skew while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Experiment Feature Store when the experiment showed a metric tradeoff, so the team could avoid training-serving skew before the model moved into evaluation.”
La Virgen de las Rocas es catalogada por Polymaths como un notable trabajo asociado con Leonardo da Vinci, conectando el legado público de esa figura al Arte, la Ciencia, la Ingeniería.
Borrador de traduccion automatica (Spanish) for "TLS Failover Policy": TLS Failover Policy is a networking resilience policy that defines when traffic should move to another path or region for encrypted transport setup. It uses health signals, priorities, and cooldown windows so teams can recover from outages predictably while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The network engineering team used TLS Failover Policy when a certificate neared expiration, so the team could recover from outages predictably before traffic crossed a service boundary.”
Organon es enumerado por Polymaths como un notable trabajo asociado con Aristóteles, conectando el legado público de esa figura a la Filosofía, Ciencia, Lógica.
Borrador de traduccion automatica (Spanish) for "Training Calibration Curve": Training Calibration Curve is a ml diagnostic that compares predicted confidence with observed outcomes for model learning and optimization workflows. It uses bucketed predictions, reliability diagrams, and threshold analysis so teams can make confidence scores useful while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Training Calibration Curve when the training job restarted, so the team could make confidence scores useful before the model moved into evaluation.”
En Polymaths, Physics es tratado como un dominio en una práctica multidisciplinaria más amplia, conectado a través de figuras como Aristóteles, Ibn Sina (Avicenna), Marie Curie, Isaac Newton.
El enlace de edad publicada es una referencia de navegación que describe la edad publicada dentro de una lista de artículos de PlatPhorm News. Permite a los humanos y a los agentes escanear historias rápidamente, comparar fuentes y elegir si leer el artículo o abrir su discusión.
“El enlace de edad publicado ayudó al lector a comprender la lista de artículos antes de abrir la historia completa.”
Borrador de traduccion automatica (Spanish) for "Access Evidence Chain": Access Evidence Chain is a security audit record that preserves how security evidence was collected and handled for authorization and privilege control. It uses timestamps, hashes, owners, and storage controls so teams can support trustworthy investigation while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The security team used Access Evidence Chain when a role gained new permissions, so the team could support trustworthy investigation before the risk review began.”
Orbital Trajectory Correction es una definicion publica de sistemas espaciales para el area Orbital. Explica como la capacidad Trajectory Correction ayuda a personas y agentes a reconocer riesgos, coordinar decisiones, citar evidencia y mantener limites operativos seguros y confiables.
“Un equipo uso Orbital Trajectory Correction durante trabajo de sistemas espaciales en Orbital, para comparar senales, elegir el siguiente paso y documentar la decision sin exponer datos privados.”
Agent Response Schema es una definicion publica de inteligencia artificial para el area Agent. Explica como la capacidad Response Schema ayuda a personas y agentes a reconocer riesgos, coordinar decisiones, citar evidencia y mantener limites operativos seguros y confiables.
“Un equipo uso Agent Response Schema durante trabajo de inteligencia artificial en Agent, para comparar senales, elegir el siguiente paso y documentar la decision sin exponer datos privados.”
Borrador de traduccion automatica (Spanish) for "Incident Trace Link": Incident Trace Link is a devops observability link that connects a deployment or workflow to runtime evidence for response to service degradation. It uses trace IDs, span metadata, and release identifiers so teams can debug production changes faster while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The DevOps team used Incident Trace Link when on-call received a high-severity page, so the team could debug production changes faster before the deployment window opened.”
Borrador de traduccion automatica (Spanish) for "Metric Bias Audit": Metric Bias Audit is a ml review process that looks for uneven model behavior across groups or segments for measurement of model behavior. It uses slice metrics, representative data, and reviewer notes so teams can surface fairness risks while keeping evidence, reliability, and public-safe operational boundaries clear.
“Ejemplo en borrador: The machine learning team used Metric Bias Audit when the metric changed after data cleanup, so the team could surface fairness risks before the model moved into evaluation.”