Official Technical Resources: Microsoft (page 16)
Official Technical Resources · Microsoft: 312 entries in total; this page lists entries 226–240.
Data, privacy, and security for Document Intelligence
This document details issues for data, privacy, and security for Document Intelligence.
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, limitations, and best practices for improving accuracy
Characteristics, Accuracy, and limitations when using the face service. Learn how to benchmark and measure accuracy when using the face 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
Data and privacy for Face
This document details issues for data, privacy, and security for Face
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 question answering
Characteristics and limitations of question answering
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 Summarization
System characteristics and limitations for summarization
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 custom named entity recognition
Characteristics and limitations for using custom named entity recognition
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 custom text classification
Learn about characteristics and limitations for using custom text classification.
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 Language in Foundry Tools
This document details issues for data and privacy for Azure Language in Foundry Tools.
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
Customer Copyright Commitment Required Mitigations
Customer Copyright Commitment Required Mitigations for Azure OpenAI in Foundry Models
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 Models sold by Azure in Microsoft Foundry
This document details issues for data, privacy, and security for Models sold by Azure
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
Overview of responsible AI practices for Azure OpenAI models
RAI overview for Azure OpenAI 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
Characteristics and limitations of Pronunciation Assessment
This article provides information on the characteristics and limitations of using Pronunciation Assessment and the considerations you should make for it's responsible use.
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: Speech Recognition and Synthesis · Multimodal Models
Link last checked: 2026-09-24
Data and Privacy for Speech to text
This document details issues for data, privacy, and security for a Speech to text.
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: Speech Recognition and Synthesis · Privacy and Data Compliance · AI Governance and Regulation
Link last checked: 2026-09-24
Disclosure design guidelines for synthetic voices
Introduction to disclosure design guidelines and assessing disclosure level.
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: Speech Recognition and Synthesis · Multimodal Models
Link last checked: 2026-09-24
Disclosure design guidelines for avatars
Introduction to disclosure design guidelines and assessing disclosure level for avatars.
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: Speech Recognition and Synthesis · Multimodal Models
Link last checked: 2026-09-24