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articles/ai-services/openai/concepts/abuse-monitoring.md

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## Modified abuse monitoring
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Some customers may want to use the Azure OpenAI Service for a use case that involves the processing of highly sensitive or highly confidential data, or otherwise may conclude that they don't want or don't have the right to permit Microsoft to store and conduct human review on their prompts and completions for abuse detection. To address these concerns, Microsoft allows customers who meet additional Limited Access eligibility criteria to apply to modify abuse monitoring by completing [this ](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu)form. Learn more about applying for modified abuse monitoring at [Limited access to Azure OpenAI Service](/legal/cognitive-services/openai/limited-access?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext), and about the impact of modified abuse monitoring on data processing at [Data, privacy, and security for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=azure-portal).
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Some customers may want to use the Azure OpenAI Service for a use case that involves the processing of highly sensitive or highly confidential data, or otherwise may conclude that they don't want or don't have the right to permit Microsoft to store and conduct human review on their prompts and completions for abuse detection. To address these concerns, Microsoft allows customers who meet additional Limited Access eligibility criteria to apply to modify abuse monitoring by completing [this](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu)form. Learn more about applying for modified abuse monitoring at [Limited access to Azure OpenAI Service](/legal/cognitive-services/openai/limited-access?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext), and about the impact of modified abuse monitoring on data processing at [Data, privacy, and security for Azure OpenAI Service](/legal/cognitive-services/openai/data-privacy?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=azure-portal).
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> [!NOTE]
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> When abuse monitoring is modified and human review is not performed, detection of potential abuse may be less accurate. Customers are notified of potential abuse detection as described above, and should be prepared to respond to such notification to avoid service interruption if possible.

articles/ai-services/openai/concepts/advanced-prompt-engineering.md

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title: Design system messages with Azure OpenAI
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description: Learn about system message design with GPT-3, GPT-35-Turbo, and GPT-4 models.
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description: Learn about system message design
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keywords: ChatGPT, GPT-4, meta prompts, chain of thought
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## What is a system message?
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## What is a system message?
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A system message is a feature-specific set of instructions or contextual frameworks given to a generative AI model (e.g. GPT4-o, GPT3.5 Turbo, etc.) to direct and improve the quality and safety of a model’s output. This is particularly helpful in situations that need certain degrees of formality, technical language, or industry-specific terms.
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A system message is a feature-specific set of instructions or contextual frameworks given to a generative AI model (e.g. GPT-4o, GPT-3.5 Turbo, etc.) to direct and improve the quality and safety of a model’s output. This is particularly helpful in situations that need certain degrees of formality, technical language, or industry-specific terms.
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There is no prescribed length. A system message can be one short sentence:

articles/ai-services/openai/concepts/customizing-llms.md

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description: Learn more about the concepts behind customizing an LLM with Azure OpenAI.
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articles/ai-services/openai/concepts/fine-tuning-considerations.md

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recommendations: false

articles/ai-services/openai/concepts/prompt-engineering.md

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description: Learn how to use prompt engineering to optimize your work with Azure OpenAI Service.
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# Prompt engineering techniques
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GPT-3, GPT-3.5, GPT-4, and GPT-4o models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text.
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GPT-3, GPT-3.5, GPT-4, and GPT-4o models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text. These techniques are note recommended for o-series models.
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While these models are extremely powerful, their behavior is also very sensitive to the prompt. This makes prompt construction an important skill to develop.
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articles/ai-services/openai/concepts/provisioned-throughput.md

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description: Learn about provisioned throughput and Azure OpenAI.
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articles/ai-services/openai/concepts/red-teaming.md

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description: 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)
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articles/ai-services/openai/concepts/system-message.md

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description: Learn about how to construct system messages also know as metaprompts to guide an AI system's behavior.
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articles/ai-services/openai/concepts/understand-embeddings.md

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articles/ai-services/openai/encrypt-data-at-rest.md

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