机器辅助翻译草稿 (Chinese) for "Scheduler Autoscaling Policy": Scheduler Autoscaling Policy is a compute control loop that changes capacity based on demand signals for placement of work onto resources. It uses metrics, thresholds, and cooldowns so teams can match resources to load while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The platform engineering team used Scheduler Autoscaling Policy when the cluster needed to place a job, so the team could match resources to load before the workload scaled up.”
机器辅助翻译草稿 (Chinese) for "BGP Traffic Shaper": BGP Traffic Shaper is a networking control mechanism that limits or prioritizes flows across links for interdomain routing. It uses queues, rate limits, and quality-of-service rules so teams can protect important traffic while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The network engineering team used BGP Traffic Shaper when a route advertisement changed, so the team could protect important traffic before traffic crossed a service boundary.”
机器辅助翻译草稿 (Chinese) for "Read URL Field": The Read URL Field is a structured metadata field that describes the read url inside a PlatPhorm News article listing. It lets humans and agents scan stories quickly, compare sources, and choose whether to read the article or open its discussion.
“示例草稿: The Read URL Field helped the reader understand the article listing before opening the full story.”
机器辅助翻译草稿 (Chinese) for "Orbital Science Window": Orbital Science Window is a space planning interval that marks when conditions are suitable for data collection for spacecraft orbit planning and station keeping. It uses target visibility, power budgets, thermal state, and downlink availability so teams can capture useful observations without breaking constraints while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Orbital Science Window when a spacecraft entered a crowded orbital shell, so the team could capture useful observations without breaking constraints before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Virginia Statute for Religious Freedom": Virginia Statute for Religious Freedom is listed by Polymaths as a notable work associated with Thomas Jefferson, connecting that figure's public legacy to Politics, Philosophy, Law.
“示例草稿: Virginia Statute for Religious Freedom appears in the Polymaths profile for Thomas Jefferson.”
机器辅助翻译草稿 (Chinese) for "Training Bias Audit": Training Bias Audit is a ml review process that looks for uneven model behavior across groups or segments for model learning and optimization workflows. 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.
“示例草稿: The machine learning team used Training Bias Audit when the training job restarted, so the team could surface fairness risks before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Pipeline Model Card": Pipeline Model Card is a ml documentation artifact that summarizes intended use, limits, and evaluation evidence for automated data and model workflow. It uses dataset notes, metric tables, and risk statements so teams can publish model behavior honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Pipeline Model Card when the pipeline missed a validation step, so the team could publish model behavior honestly before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "Zero Trust Phishing Resistance": Zero Trust Phishing Resistance is a security identity control that reduces success of credential theft attacks for continuous verification model. It uses passkeys, hardware-backed factors, and origin checks so teams can protect sign-in flows while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The security team used Zero Trust Phishing Resistance when a device changed posture, so the team could protect sign-in flows before the risk review began.”
机器辅助翻译草稿 (Chinese) for "GPU Checkpoint Restore": GPU Checkpoint Restore is a compute recovery workflow that resumes work from a saved state for accelerated compute for parallel workloads. 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.
“示例草稿: The platform engineering team used GPU Checkpoint Restore when the training job requested more memory, so the team could recover long-running work before the workload scaled up.”
机器辅助翻译草稿 (Chinese) for "Infrastructure Runbook Check": Infrastructure Runbook Check is a devops operational test that confirms that documented procedures still work for cloud resources and platform wiring. It uses dry runs, screenshots, and command validation so teams can keep response playbooks current while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The DevOps team used Infrastructure Runbook Check when a new region was added, so the team could keep response playbooks current before the deployment window opened.”
机器辅助翻译草稿 (Chinese) for "Lunar Attitude Control": Lunar Attitude Control is a space subsystem that keeps a spacecraft pointed correctly for power, thermal safety, communication, or science for Moon surface and cislunar mission operations. It uses sensors, reaction wheels, thrusters, and control laws so teams can maintain pointing without exceeding constraints while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Lunar Attitude Control when the lander crossed into a polar shadow region, so the team could maintain pointing without exceeding constraints before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Dataset Bias Audit": Dataset Bias Audit is a ml review process that looks for uneven model behavior across groups or segments for labeled and unlabeled data used for learning. 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.
“示例草稿: The machine learning team used Dataset Bias Audit when the dataset received a new batch, so the team could surface fairness risks before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "DNS Traffic Shaper": DNS Traffic Shaper is a networking control mechanism that limits or prioritizes flows across links for name resolution and delegation. It uses queues, rate limits, and quality-of-service rules so teams can protect important traffic while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The network engineering team used DNS Traffic Shaper when a resolver returned stale data, so the team could protect important traffic before traffic crossed a service boundary.”
机器辅助翻译草稿 (Chinese) for "Martian Recovery Mode": Martian Recovery Mode is a space resilience pattern that moves a spacecraft or mission system into a known safe operating state for Mars relay, rover, and entry operations. It uses health checks, fallback commands, and restart procedures so teams can restore control after anomalies while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The mission team used Martian Recovery Mode when the rover started a high-latency science pass, so the team could restore control after anomalies before the next mission decision point.”
机器辅助翻译草稿 (Chinese) for "Guardrail Tool Permission": Guardrail Tool Permission is a ai access control that decides which tools an AI workflow may call for policy controls around model input and output. It uses operation allowlists, user intent checks, and protected-action gates so teams can block unsafe automation while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The AI platform team used Guardrail Tool Permission when the model tried to include private context, so the team could block unsafe automation before the agent workflow reached production.”
机器辅助翻译草稿 (Chinese) for "Polymathic Psychology": In Polymaths, Psychology is treated as one domain in a wider multidisciplinary practice, connected through figures such as Ibn Sina (Avicenna).
“示例草稿: Polymathic psychology becomes more powerful when it connects with other domains instead of remaining isolated.”
机器辅助翻译草稿 (Chinese) for "Polymathic Painting": In Polymaths, Painting is treated as one domain in a wider multidisciplinary practice, connected through figures such as Zhang Heng.
“示例草稿: Polymathic painting becomes more powerful when it connects with other domains instead of remaining isolated.”
机器辅助翻译草稿 (Chinese) for "Serverless Isolation Boundary": Serverless Isolation Boundary is a compute security boundary that separates workloads so one cannot affect another unexpectedly for event-driven function execution. It uses namespaces, sandboxes, and access controls so teams can reduce cross-workload risk while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The platform engineering team used Serverless Isolation Boundary when the function received a traffic burst, so the team could reduce cross-workload risk before the workload scaled up.”
机器辅助翻译草稿 (Chinese) for "Fine-Tuning Evaluation Harness": Fine-Tuning Evaluation Harness is a ml test system that runs repeatable checks against model behavior for adaptation of a model to a domain. It uses fixtures, metrics, thresholds, and regression reports so teams can compare releases with evidence while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The machine learning team used Fine-Tuning Evaluation Harness when the fine-tuning run used curated examples, so the team could compare releases with evidence before the model moved into evaluation.”
机器辅助翻译草稿 (Chinese) for "GPU Runtime Profile": GPU Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for accelerated compute for parallel workloads. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.
“示例草稿: The platform engineering team used GPU Runtime Profile when the training job requested more memory, so the team could target optimization work before the workload scaled up.”