Define the new internet.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
Look up the words people use online, add the ones we missed, and help make the internet easier to understand.
2,337 definitions
Pipeline Evaluation Harness is a ml test system that runs repeatable checks against model behavior for automated data and model workflow. 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.
“The machine learning team used Pipeline Evaluation Harness when the pipeline missed a validation step, so the team could compare releases with evidence before the model moved into evaluation.”
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.
“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.”
Canary Artifact Signature is a devops supply-chain record that proves that an artifact came from an expected build path for small-scope production rollout. It uses cryptographic signatures, provenance, and verification so teams can trust deployed packages while keeping evidence, reliability, and public-safe operational boundaries clear.
“The DevOps team used Canary Artifact Signature when the first traffic slice received the build, so the team could trust deployed packages before the deployment window opened.”
CD Build Gate is a devops quality gate that blocks promotion when required checks fail for deployment automation and promotion. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“The DevOps team used CD Build Gate when the release moved toward production, so the team could prevent broken releases before the deployment window opened.”
CD Rollback Plan is a devops recovery plan that defines how to return to a known good version for deployment automation and promotion. It uses version pins, database notes, and operator steps so teams can recover quickly from bad changes while keeping evidence, reliability, and public-safe operational boundaries clear.
“The DevOps team used CD Rollback Plan when the release moved toward production, so the team could recover quickly from bad changes before the deployment window opened.”
Environment Build Gate is a devops quality gate that blocks promotion when required checks fail for configuration for a runtime stage. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“The DevOps team used Environment Build Gate when staging and production drifted, so the team could prevent broken releases before the deployment window opened.”
Metric Embedding Refresh is a ml index workflow that updates vector representations after source data changes for measurement of model behavior. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.
“The machine learning team used Metric Embedding Refresh when the metric changed after data cleanup, so the team could keep retrieval results current before the model moved into evaluation.”
Fine-Tuning Embedding Refresh is a ml index workflow that updates vector representations after source data changes for adaptation of a model to a domain. It uses batch jobs, backfills, and index validation so teams can keep retrieval results current while keeping evidence, reliability, and public-safe operational boundaries clear.
“The machine learning team used Fine-Tuning Embedding Refresh when the fine-tuning run used curated examples, so the team could keep retrieval results current before the model moved into evaluation.”
Artifact Build Gate is a devops quality gate that blocks promotion when required checks fail for build output and package delivery. It uses tests, lint, security scans, and policy rules so teams can prevent broken releases while keeping evidence, reliability, and public-safe operational boundaries clear.
“The DevOps team used Artifact Build Gate when the container image was signed, so the team could prevent broken releases before the deployment window opened.”
Metric Data Split is a ml experimental control that separates examples for training, validation, and testing for measurement of model behavior. It uses randomization rules, leakage checks, and seed tracking so teams can measure generalization honestly while keeping evidence, reliability, and public-safe operational boundaries clear.
“The machine learning team used Metric Data Split when the metric changed after data cleanup, so the team could measure generalization honestly before the model moved into evaluation.”