Azure AI announces Prompt Shields for Jailbreak and Indirect prompt injection attacks
Our Azure OpenAI Service and Azure AI Content Safety teams are excited to launch a new Responsible AI capability called Prompt Shields. Prompt Shields protects applications powered by Foundation Models from two types of attacks: direct (jailbreak) and indirect attacks, both of which are now available in Public Preview.Azure OpenAI Best Practices Insights from Customer Journeys
When integrating Azure OpenAI’s powerful models into your production environment, it’s essential to follow best practices to ensure security, reliability, and scalability. Azure provides a robust platform with enterprise capabilities that, when leveraged with OpenAI models like GPT-4, DALL-E 3, and various embedding models, can revolutionize how businesses interact with AI. This guidance document contains best practices for scaling OpenAI applications within Azure, detailing resource organization, quota management, rate limiting, and the strategic use of Provisioned Throughput Units (PTUs) and Azure API Management (APIM) for efficient load balancing.
Explore Azure AI Services: Curated list of prebuilt models and demos
Unlock the potential of AI with Azure's comprehensive suite of prebuilt models and demos. Whether you're looking to enhance speech recognition, analyze text, or process images and documents, Azure AI services offer ready-to-use solutions that make implementation effortless. Explore the diverse range of use cases and discover how these powerful tools can seamlessly integrate into your projects. Dive into the full catalogue of demos and start building smarter, AI-driven applications today.
Intelligent Load Balancing with APIM for OpenAI: Weight-Based Routing
Weightage: There is no direct feature capablities in APIM for weightage based routing.I have tried achieve same results using custom logic with APIM policies Selection Process: Backend logic used in this policy is based on weighted selection method to choose an endpoint route for retry.endpoint with higher weights are more likely to be chosen, but each endpoints route has at least some chance of being selected. This is because the selection is based on a random number that is compared against cumulative weights, which means the selection process inherently favors routes with higher weights due to the way cumulative weights are calculated and utilizedCorrection capability helps revise ungrounded content and hallucinations
Today, we are excited to announce a preview of "correction," a new capability within Azure AI Content Safety's groundedness detection feature. With this enhancement, groundedness detection not only identifies inaccuracies in AI outputs but also corrects them, fostering greater trust in generative AI technologies.
Share Your Experience with Azure AI and Support a Charity
AI is transforming how leaders tackle problem-solving and creativity across different industries. From creating realistic images to generating human-like text, the potential of large and small language model-powered applications is vast. Our goal at Microsoft is to continuously enhance our offerings and provide the best safe, secure, and private AI services and machine learning platform for developers, IT professionals and decision-makers who are paving the way for AI transformations. Are you using Azure AI to build your generative AI apps? We’re excited to invite our valued Azure AI customers to share their experiences and insights on Gartner Peer Insights. Your firsthand review not only helps fellow developers and decision-makers navigate their choices but also influences the evolution of our AI products. Write a Review: Microsoft Gartner Peer Insights https://gtnr.io/JK8DWRoL0.
