Official Technical Resources: Microsoft (page 15)
Official Technical Resources · Microsoft: 312 entries in total; this page lists entries 211–225.
Harm categories and severity levels in Microsoft Foundry
Learn about the harm categories and severity levels used by the content safety system in Microsoft Foundry to detect and filter harmful content.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Guardrails · AI Governance and Regulation
Link last checked: 2026-09-24
Default Guardrail policies for Azure OpenAI
Learn about the default Guardrail policies that Azure OpenAI uses to flag content and ensure responsible use of the service.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Guardrails · AI Governance and Regulation
Link last checked: 2026-09-24
Microsoft Foundry fine-tuning considerations
Learn more about what you should take into consideration before fine-tuning with Microsoft Foundry.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Fine-tuning · Model Evaluation and Benchmarks
Link last checked: 2026-09-24
Prompt engineering techniques
Learn how to use prompt engineering to optimize your work with Azure OpenAI.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Prompt Engineering · System Prompts and Role Prompting
Link last checked: 2026-09-24
Prompt transformation
Learn about the prompt transformation feature in Azure OpenAI image generation models, how it works, and why it's necessary.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Prompt Engineering · System Prompts and Role Prompting
Link last checked: 2026-09-24
Planning red teaming for large language models (LLMs) and their applications
Learn about how red teaming and adversarial testing are an essential practice in the responsible development of systems and features using large language models (LLMs)
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Red Teaming · AI Guardrails · AI Governance and Regulation
Link last checked: 2026-09-24
Safety system message templates
Use these safety system message templates as a starting point to reduce harmful and ungrounded outputs in your Azure OpenAI apps.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Prompt Engineering · System Prompts and Role Prompting
Link last checked: 2026-09-24
Data, privacy, and security for Foundry Agent Service
This document details issues for data, privacy, and security for the Foundry Agent Service
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Privacy and Data Compliance · AI Governance and Regulation
Link last checked: 2026-09-24
Characteristics and limitations of Anomaly Detector
Characteristics and limitations of using Anomaly Detector and Metrics Advisor
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Governance and Regulation · Bias and Fairness · AI Interpretability
Link last checked: 2026-09-24
Characteristics and limitations for using conversational language understanding
Characteristics and limitations for using conversational language understanding.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Governance and Regulation · Bias and Fairness · AI Interpretability
Link last checked: 2026-09-24
Characteristics and limitations for using Image Analysis
Characteristics, accuracy, and limitations when using Image Analysis service.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Governance and Regulation · Bias and Fairness · AI Interpretability
Link last checked: 2026-09-24
Capabilities and limitations of optical character recognition
Characteristics and limitations for optical character recognition (OCR) of images and documents with printed and handwritten text using the Azure Vision in Foundry Tools API.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Governance and Regulation · Bias and Fairness · AI Interpretability
Link last checked: 2026-09-24
Data, privacy, and security for Azure AI Content Safety
This document details issues for data, privacy, and security for Azure AI Content Safety.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Privacy and Data Compliance · AI Governance and Regulation
Link last checked: 2026-09-24
Content provenance for Foundry models
Content provenance
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI-generated Content Detection and Watermarking · AI Governance and Regulation
Link last checked: 2026-09-24
Data, privacy, and security for Content Understanding
This document details issues for data, privacy, and security for Content Understanding.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Privacy and Data Compliance · AI Governance and Regulation
Link last checked: 2026-09-24