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AI and Machine Learning verified Output moderation Output moderation is the safety review applied to generated model responses before they are shown or acted on. In Azure OpenAI and Azure AI Content Safety patterns, classifiers or configured filters evaluate completions for harmful categories, policy matches, and blocked content so applications can handle unsafe responses. Responsible AI and safety intermediate 5 commands Aliases: completion moderation, response moderation, generated-output moderation, AI output filtering Quick peek Open full term page

AI and Machine Learning premium Azure AI Content Safety Azure AI Content Safety is the Azure AI service used to detect harmful text and image content before it reaches users, moderators, or automated workflows. In Azure, teams encounter it when applications accept user posts, comments, uploads, prompts, or model outputs that need moderation and policy review. The useful question is what behavior it proves, Responsible AI advanced 4 commands Aliases: Content Safety, Azure Content Safety, harm detection, content moderation API Quick peek Open full term page

AI and Machine Learning verified Responsible AI Microsoft Learn describes Responsible AI as an approach to developing, assessing, and deploying AI systems safely, ethically, and with trust. In Azure Machine Learning, it connects fairness, reliability, privacy, security, transparency, accountability, and operational tooling so teams can evaluate models before production use. Responsible AI fundamentals 8 commands Aliases: Responsible Artificial Intelligence, RAI, trustworthy AI, AI governance, responsible machine learning Quick peek Open full term page

AI and Machine Learning verified Responsible AI policy Microsoft Learn guidance for Responsible AI practices in Azure OpenAI emphasizes defined content policies, misuse detection, user blocking mechanisms, human review, safety evaluation, and escalation. In Azure, a Responsible AI policy is the operating rule set that turns those practices into enforceable product behavior. Azure OpenAI intermediate 7 commands Aliases: AI safety policy, Azure OpenAI responsible AI policy, generative AI policy, AI acceptable use policy, Responsible AI guardrails Quick peek Open full term page

AI and Machine Learning verified Responsible AI dashboard Microsoft Learn describes the Responsible AI dashboard as a single interface for putting Responsible AI into practice in Azure Machine Learning. It brings together tools for model debugging, cohort analysis, interpretability, counterfactuals, causal insights, error analysis, and shareable scorecards for registered models. Azure Machine Learning intermediate 7 commands Aliases: RAI dashboard, Responsible AI insights, model debugging dashboard, Responsible AI scorecard, fairness dashboard Quick peek Open full term page

AI and Machine Learning field-manual-ready ML responsible AI dashboard An ML responsible AI dashboard helps teams inspect model behavior, errors, explanations, fairness, and related review evidence. Azure Machine Learning intermediate 4 commands Aliases: Azure ML responsible AI dashboard, RAI dashboard, Responsible AI dashboard Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry Create a governed project boundary where AI teams can build agents, evaluations, files, and model deployments without unmanaged sprawl.; Compare, evaluate, and approve model deployments before a generative AI feature is AI platform fundamentals 5 commands Aliases: AI Foundry, Microsoft Foundry, Foundry resource, Foundry project, Azure AI Foundry, azure ai foundry Quick peek Open full term page

AI and Machine Learning premium Azure AI services Azure AI services is the family of Azure cloud AI APIs and resources, surfaced through Foundry Tools, for vision, speech, language, translation, content, and generative scenarios. AI services fundamentals 4 commands Aliases: AI services, Azure AI services account, Cognitive Services, Foundry Tools Quick peek Open full term page

AI and Machine Learning premium AI red teaming AI red teaming is the practice of probing a generative AI system with adversarial prompts, attack strategies, and risk categories to discover unsafe behavior, jailbreak weaknesses, and harmful-output paths before or after deployment. Responsible AI advanced 3 commands Aliases: AI Red Teaming Agent, red team scan, adversarial AI testing, LLM red teaming Quick peek Open full term page

AI and Machine Learning premium Content Safety the Azure AI service used to detect harmful text and image content before it reaches users or workflows Responsible AI intermediate 3 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning field-manual-complete Private endpoint for AI service A private endpoint for an AI service is the private network doorway to an Azure AI services account. Applications still call the service endpoint they are configured to use, but clients inside the linked network can resolve that name to a private IP instead of reaching across a public path. It is useful when document processing, language analysis, speech, content safety, or vision workloads handle sensitive data. It does not replace authentication, keys, managed identity, or responsible AI controls. AI platform and search intermediate 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry project An Azure AI Foundry project is the working area where a team builds and organizes an AI application inside Microsoft Foundry. It keeps related agents, evaluations, files, indexes, tools, connections, and model usage together instead of scattering them across a shared portal. Think of it as the project boundary for one AI product, prototype, or team. It is useful because AI work quickly becomes messy: prompts, test data, model deployments, safety checks, and access decisions all need a home with ownership and repeatable operations. AI platform advanced 4 commands Aliases: AI Foundry project, AI project, Foundry project, Microsoft Foundry project Quick peek Open full term page

AI and Machine Learning premium Azure AI Language Azure AI Language is the Azure natural-language processing service for analyzing and understanding text with prebuilt and customizable language capabilities. AI services intermediate 4 commands Aliases: Azure Language, Azure Language in Foundry Tools, Azure Language service, Language in Foundry Tools, Language service Quick peek Open full term page

AI and Machine Learning premium Azure AI metrics Azure AI metrics is the measurable signals used to observe Azure AI applications, model endpoints, agents, evaluations, safety checks, and business outcomes. Azure AI services intermediate 4 commands Aliases: AI metrics, AI service metrics, Azure AI Metrics Advisor, Azure Monitor metrics for AI, Metrics Advisor, time series anomaly detection Quick peek Open full term page

AI and Machine Learning premium Azure AI services account An Azure resource that provides endpoints, keys, identity, networking, billing, and monitoring for one or more Azure AI service capabilities. Azure AI services fundamentals 4 commands Aliases: AI services account, Azure AI multi-service resource, Foundry resource, Microsoft.CognitiveServices account Quick peek Open full term page

AI and Machine Learning premium AI evaluation AI evaluation is the Microsoft Foundry process of testing a generative AI model, agent, or application against a dataset and measuring its quality, safety, and task performance with built-in or custom evaluators. Microsoft Foundry intermediate 3 commands Aliases: Azure AI evaluation, Foundry evaluation, generative AI evaluation, model evaluation Quick peek Open full term page

AI and Machine Learning command-rich Data source in AI Search Data source in AI Search is documented by Microsoft as part of the Azure AI Search area in Azure. Azure AI Search intermediate 6 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning template-specs-upgraded Safety system message Microsoft Learn explains that safety system messages guide Azure OpenAI model behavior, improve response quality, and reduce the likelihood of harmful outputs. They are one layer in a broader safety strategy and are also described as system prompts or metaprompts. Microsoft Foundry intermediate 5 commands Aliases: Azure OpenAI safety system message, safety metaprompt, system prompt safety guidance, Foundry safety message, AI safety instructions Quick peek Open full term page

AI and Machine Learning premium Azure AI Search index An Azure AI Search index is the place where your application searches. It is not just a pointer to a database or blob container. It is a separate searchable structure with documents, fields, and rules for how text, filters, facets, semantic ranking, and vectors behave. If the index schema is wrong, the search experience feels wrong even when the source data is good. Developers and operators use indexes to make. AI platform and search intermediate 5 commands Aliases: Azure AI Search index, search index, AI Search index, azure-ai-search-index Quick peek Open full term page

AI and Machine Learning premium Azure AI Search indexer An Azure AI Search indexer is the automated worker that fills a search index from another data source. Instead of your application pushing every document into Azure AI Search, the indexer pulls from places such as Blob Storage, Azure SQL, Cosmos DB, or Data Lake Storage. It can map fields, detect changes, crack documents, and run enrichment skills before writing searchable documents. It is useful when source data changes regularly. AI platform and search intermediate 5 commands Aliases: Azure AI Search indexer, search indexer, indexer, azure-ai-search-indexer Quick peek Open full term page

AI and Machine Learning premium AI connection AI connection is a Microsoft Foundry project connection that links the project to an external or Azure resource such as models, storage, search, or services. In everyday Azure work, teams use it to let AI applications and agents use approved resources without every prototype hardcoding endpoints and credentials. The useful evidence is connection name, target AI platform intermediate 4 commands Aliases: Foundry connection, AI project connection, connected resource, AI service connection Quick peek Open full term page

AI and Machine Learning premium Azure AI Foundry hub Azure AI Foundry hub is the classic Foundry hub resource used to group AI projects that share common security, data access, connections, and platform settings. In Azure, teams encounter it when teams need hub-based projects for selected Foundry and Azure Machine Learning scenarios such as fine-tuning, shared connections, and custom ML work. The useful question AI platform advanced 4 commands Aliases: AI Hub, Foundry AI Hub, hub-based project, Azure AI hub Quick peek Open full term page

AI and Machine Learning premium Azure AI Search Azure AI Search is a managed retrieval service for full-text, vector, hybrid, and semantic search across application and enterprise content. It provides search services, indexes, indexers, skillsets, ranking features, security controls, and APIs used by apps, copilots, and knowledge portals. Search fundamentals 4 commands Aliases: Azure AI Search, AI Search, Azure Cognitive Search, enterprise search, vector search, hybrid search, semantic search, Search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search data source Azure AI Search data source is the connection definition an Azure AI Search indexer uses to read content from a supported external data store. AI platform and search intermediate 4 commands Aliases: Search data source, SearchIndexerDataSourceConnection, data source connection, indexer data source, search data source connection Quick peek Open full term page

AI and Machine Learning premium Azure AI Search service Azure AI Search service is the Azure resource that hosts Azure AI Search indexes, indexers, skillsets, keys, capacity, networking, and query endpoints. AI platform and search intermediate 4 commands Aliases: AI Search resource, AI Search service, Azure Search service, Search service, search service Quick peek Open full term page

AI and Machine Learning premium Azure AI Search skillset Azure AI Search skillset is a reusable Azure AI Search enrichment object that applies built-in or custom processing during indexer execution. AI platform and search intermediate 4 commands Aliases: AI enrichment skillset, Search skillset, cognitive skillset, skillset Quick peek Open full term page

AI and Machine Learning premium Azure AI Speech The Azure speech service for converting speech to text, text to speech, speech translation, pronunciation assessment, and related speech-enabled capabilities. AI services intermediate 4 commands Aliases: Azure Speech, Speech in Foundry Tools, Speech service, Speech-to-text Quick peek Open full term page

AI and Machine Learning premium Azure AI Translator A cloud-based machine translation service for translating text and documents across supported languages through REST APIs and client libraries. AI services intermediate 4 commands Aliases: Azure Translator, Document Translation, Text Translation, Translator Quick peek Open full term page

AI and Machine Learning premium Azure AI Vision The Azure vision service that analyzes images and visual content for tasks such as OCR, object information, captions, tags, and image understanding. AI services intermediate 4 commands Aliases: Azure Vision, Computer Vision, Image Analysis, Vision in Foundry Tools Quick peek Open full term page

AI and Machine Learning premium Multi-service AI account Multi-service AI account means a shared Azure AI services account for applications that need several supported AI capabilities from one governed endpoint boundary. You see it when teams connect language, vision, speech, translation, or content-understanding features to production applications. Think of it as one managed account boundary for several AI capabilities, not one unlimited permission bucket. It matters because the setting changes how teams design, secure, operate, and troubleshoot the workload. Before changing it in production, know the owner, dependency, evidence, expected result, and rollback path. Azure AI services intermediate 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Multi-service AI resource Multi-service AI resource means an Azure AI resource that exposes supported AI service capabilities through one managed resource object. You see it when teams build applications that combine language, vision, speech, translation, or content services without creating a separate resource for every feature. Think of it as one Azure resource boundary for supported AI capabilities, with identity, network, monitoring, and billing attached. It matters because the setting changes how teams design, secure, operate, and troubleshoot the workload. Before changing it in production, know the owner, dependency, evidence, expected result, and rollback path. Azure AI services fundamentals 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium AI quota AI quota is the Azure allocation that limits model deployment capacity, usually by subscription, region, model, and deployment type, using measures such as tokens per minute, requests per minute, concurrent requests, or provisioned throughput. Microsoft Foundry intermediate 3 commands Aliases: Foundry quota, Azure OpenAI quota, model quota, TPM quota, RPM quota Quick peek Open full term page

Monitoring and Observability premium AI service diagnostic settings AI service diagnostic settings are Azure Monitor settings on an Azure AI or Foundry Tools resource that route resource logs and platform metrics to destinations such as Log Analytics, Storage, or Event Hubs for investigation and retention. Azure Monitor intermediate 3 commands Aliases: Azure AI diagnostic settings, Foundry Tools diagnostic logging, Cognitive Services diagnostic settings, AI resource logs Quick peek Open full term page

AI and Machine Learning premium AI service endpoint An AI service endpoint is the HTTPS base address that applications use to call an Azure AI or Foundry Tools resource. It identifies the resource, region or custom subdomain, and may resolve through public DNS or a private endpoint. Azure AI services fundamentals 3 commands Aliases: Azure AI endpoint, Cognitive Services endpoint, Foundry Tools endpoint, AI resource URL Quick peek Open full term page

AI and Machine Learning premium AI service key An AI service key is a secret access key for an Azure AI service resource. Clients pass it, commonly with the Ocp-Apim-Subscription-Key header, to authenticate API requests when key-based authentication is used. Azure AI services fundamentals 3 commands Aliases: Azure AI service key, Cognitive Services key, Ocp-Apim-Subscription-Key, resource key Quick peek Open full term page

AI and Machine Learning premium AI services account key An AI services account key is a secret key for a multi-service Azure AI or Microsoft Foundry resource. It can authenticate requests for supported services tied to that resource, making storage, rotation, and access control especially important. Azure AI services intermediate 3 commands Aliases: multi-service account key, Foundry resource key, AIServices account key, Cognitive Services account key Quick peek Open full term page

AI and Machine Learning premium AI services endpoint An AI services endpoint is the base URL for a multi-service Azure AI or Microsoft Foundry resource. Applications combine this endpoint with a supported API path and authentication method to call the resource. Azure AI services fundamentals 3 commands Aliases: multi-service endpoint, Foundry resource endpoint, AIServices endpoint, Cognitive Services endpoint Quick peek Open full term page

AI and Machine Learning premium AI services resource An AI services resource is the Azure resource, commonly Microsoft.CognitiveServices/accounts with kind AIServices, that provides the governance scope for AI service access, networking, billing, monitoring, keys, endpoints, model deployments, projects, and related configuration. Azure AI services fundamentals 3 commands Aliases: Azure AI services resource, Foundry resource, AIServices resource, Cognitive Services account Quick peek Open full term page

AI and Machine Learning premium AI token An AI token is a unit of text processed by a language model. Azure AI and Foundry model quotas, cost, and rate limits commonly use tokens to measure prompt input, generated output, and throughput such as tokens per minute. Azure OpenAI and Foundry Models fundamentals 3 commands Aliases: model token, LLM token, input token, output token, TPM Quick peek Open full term page

AI and Machine Learning premium AI tracing AI tracing captures execution telemetry for generative AI applications and agents, including model calls, prompts, tool invocations, retrieval steps, latency, token usage, errors, and run relationships so teams can debug and monitor behavior in Microsoft Foundry and Azure Monitor. AI observability intermediate 3 commands Aliases: Foundry tracing, agent tracing, LLM tracing, AI distributed tracing Quick peek Open full term page

AI and Machine Learning verified Provisioned throughput for AI Provisioned throughput for AI in Microsoft Foundry allocates provisioned throughput units to supported model deployments. PTUs give reserved processing capacity for predictable latency and throughput, with deployment choices such as regional, data-zone, or global provisioned capacity and separate reservation-based billing options. Microsoft Foundry advanced 6 commands Aliases: No aliases yet Quick peek Open full term page

Integration verified Receive-and-delete mode A integration pattern or service capability in Messaging that helps teams connect services reliably without tightly coupling every component with clearer ownership, safety, and operational context. Messaging fundamentals 5 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning complete Single-service AI account An Azure AI services resource dedicated to one service kind, with its own endpoint, keys, region, SKU, monitoring, and billing. AI services intermediate 5 commands Aliases: single service AI resource, single-service Azure AI resource, dedicated AI services account Quick peek Open full term page

Integration verified Receive and delete Receive and delete is an Azure Service Bus receive mode where the broker considers a message settled as soon as it sends the message to the receiver. If transfer or processing fails afterward, the message is lost instead of being redelivered. Azure Service Bus intermediate 5 commands Aliases: ReceiveAndDelete, receive-and-delete mode, destructive read, at-most-once receive Quick peek Open full term page

AI and Machine Learning premium Face API The Face API is an Azure AI service API that provides face detection, recognition, verification, identification, grouping, and related face analysis capabilities. Teams use it to build applications that detect faces in images, compare faces, verify identity scenarios, support liveness workflows, or organize face-related image data under approved responsible AI controls. It is not a general computer vision labeler, proof of identity by itself, a surveillance policy, or permission to use biometric capabilities without legal, privacy, and access review. Azure AI services intermediate 6 commands Aliases: Azure AI Face, Azure Face API, Face service Quick peek Open full term page

AI and Machine Learning premium Face service Face service is an Azure AI service that provides APIs for face detection, face analysis, verification, identification, grouping, and liveness-related workflows under approved access controls. Teams use it to build applications that detect faces in images, compare face evidence, verify approved identity scenarios, support liveness checks, or manage face lists within privacy and responsible AI controls. It is not a general image classification service, legal approval to process biometric data, a replacement for human identity review, or a guarantee that every face decision is correct. Azure AI services intermediate 6 commands Aliases: Azure AI Face, Azure AI Face service, Azure Face service, Face API, Azure AI services Face Quick peek Open full term page

AI and Machine Learning premium Abuse monitoring Abuse monitoring is the safety layer that looks for harmful or policy-violating use of AI services. It is not a performance feature; it exists to help detect misuse, protect the service, and support responsible operation of model deployments. Azure OpenAI intermediate 4 commands Aliases: No aliases yet Quick peek Open full term page

AI and Machine Learning premium Deployment type Deployment type is the Azure AI or Microsoft Foundry model hosting option, such as standard, global, data-zone, regional, batch, serverless, or provisioned deployment, that determines availability, data processing location, capacity model, cost, and operational behavior. Microsoft Foundry intermediate 4 commands Aliases: Microsoft Foundry deployment type, Azure AI deployment type, model deployment type, Foundry Models deployment type Quick peek Open full term page

AI and Machine Learning premium Function calling Function calling is an AI application pattern where a model chooses a developer-defined tool and returns structured arguments so the application can call real business logic. Teams use it to let assistants retrieve data, create tickets, schedule work, search systems, or call APIs while the application remains responsible for execution and validation. In daily Azure work, it shows up when engineers build agents, connect chat to backend tools, audit model-selected actions, validate JSON arguments, or debug why a model called the wrong function. Azure OpenAI advanced 4 commands Aliases: tool calling, OpenAI function calling, model tool call Quick peek Open full term page

AI and Machine Learning premium Groundedness detection Groundedness detection checks whether a generated text response is supported by provided source material and flags responses that appear ungrounded or inconsistent with that material. Azure AI Content Safety advanced 4 commands Aliases: groundedness filter, ungroundedness detection, AI groundedness check Quick peek Open full term page