Insecure output handling – Security and Privacy Considerations for Gen AI – Building Safe and Secure LLMs

Insecure output handling In the previous examples, we learned about a few various security risks, threats, and exploits, especially against …

Key principles of RAI – Responsible Development of AI Solutions: Building with Integrity and Care

Key principles of RAI Figure 9.1 – Responsible AI principles Microsoft has established a Responsible AI Standard, presenting a comprehensive …

Azure OpenAI service API keys – Security and Privacy Considerations for Gen AI – Building Safe and Secure LLMs

Azure OpenAI service API keys The Azure OpenAI service itself, along with OpenAI, uses API keys for applications to access …

Transparency – Responsible Development of AI Solutions: Building with Integrity and Care

Transparency This principledemands clarity on how AI systems make decisions or reach conclusions. For example, a credit scoring AI system …

Building applications using a responsible AI-first approach – Responsible Development of AI Solutions: Building with Integrity and Care

Building applications using a responsible AI-first approach In this section, we will explore the development of generative AI applications with …

Building/augmenting loop – Responsible Development of AI Solutions: Building with Integrity and Care

Building/augmenting loop Thisstage is part of the second loop. After the team identifies the desired models, in this stage, the …

Role of AI architects and leadership – Responsible Development of AI Solutions: Building with Integrity and Care

Role of AI architects and leadership AI architects and leaders play a pivotal role in building responsible AI practices within …

AI, the cloud, and the law – understanding compliance and regulations – Responsible Development of AI Solutions: Building with Integrity and Care

AI, the cloud, and the law – understanding compliance and regulations In this section, we will discuss compliance in the …