Deploying GPT-4o AI Chat app on Azure via Azure AI Services – a step-by-step guide
Are you ready to revolutionize your business with cutting-edge AI technology? Dive into our comprehensive step-by-step guide on deploying a GPT-4o AI Chat app using Azure AI Services. Discover how to harness the power of advanced natural language processing to create interactive, human-like chat experiences. From setting up your Azure account to deploying your AI model and customizing your chat app, this guide covers it all. Unleash the potential of AI in your business and stay ahead of the curve with the latest advancements from Microsoft Azure. Don’t miss out on this opportunity to transform your workflows and elevate customer interactions to new heights!How to use Azure Open AI to Enhance Your Data Analysis in Power BI
Learn how to take your data analysis to the next level with Azure Open AI. This article provides step-by-step guidance on how to integrate Open AI with Power BI and Azure Machine Learning. Enhance your data insights and make better-informed decisions. Read now to take advantage of the latest innovations in data analysis.Introduction to Monitoring Azure OpenAI Service
Monitoring data Azure OpenAI collects monitoring data as: Activity log Alerts Metrics Diagnostic settings Insights Collection and routing Platform metrics and the Activity log are collected automatically Can be routed to other locations by using a diagnostic setting Configure diagnostic settings in the Azure portal Implement logging and monitoring for Azure OpenAI models - Architecture Diagram that shows an architecture that provides monitoring and logging for Azure OpenAI. Client applications access Azure OpenAI endpoints to perform text generation (completions) and model training (fine-tuning). Azure Application Gateway provides a single point of entry to Azure OpenAI models and provides load balancing for APIs. Azure API Management enables security controls and auditing and monitoring of the Azure OpenAI models. a. In API Management, enhanced-security access is granted via Azure Active Directory (Azure AD) groups with subscription-based access permissions. b. Auditing is enabled for all interactions with the models via Azure Monitor request logging. c. Monitoring provides detailed Azure OpenAI model usage KPIs and metrics, including prompt information and token statistics for usage traceability. API Management connects to all Azure resources via Azure Private Link. This configuration provides enhanced security for all traffic via private endpoints and contains traffic in the private network. Multiple Azure OpenAI instances enable scale-out of API usage to ensure high availability and disaster recovery for the service. More details : https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/monitoring#monitoring-dataIntroduction to Planning and Managing Costs of Azure OpenAI
& Manage Costs of Azure OpenAI Service Planning to manage costs for Azure OpenAI Service Estimate costs Understand the full billing model Other costs that might accrue with Azure OpenAI Service Using Azure Prepayment with Azure OpenAI Service Monitor costs Monitor costs from Cost analysis under Resource Management. To view Azure OpenAI costs in cost analysis: Sign in to the Azure portal. Select one of your Azure OpenAI resources. Under Resource Management select Cost analysis By default cost analysis is scoped to the individual Azure OpenAI resource. Screenshot of cost analysis dashboard scoped to an Azure OpenAI resource. Creating budgets Create alerts that notifies of overspending risks. Budgets can be created with filters for specific resources or services in Azure if you want more granularity present in your monitoring. Filters help ensure that you don't accidentally create new resources that cost you additional money. For more information about the filter options available when you create a budget, see Group and filter options.Master Generative AI with Azure OpenAI Service: A Comprehensive Guide for Students
Dive into the cutting-edge technology of Generative AI with our detailed guide. From understanding the role of large language models to building powerful applications with Azure OpenAI Service, this guide has everything you need. Plus, participate in our Azure OpenAI Cloud Skills Challenge and compete with peers globally while enhancing your technical skills. Start your journey with Generative AI today!Revolutionize Education with Azure OpenAI: PolyGlot-Edu Generator
Explore the groundbreaking PolyGlot-Edu Generator, developed by Antonio Bucchiarone in collaboration with Microsoft Azure's OpenAI services. This cutting-edge tool empowers educators worldwide with AI-driven exercises, allowing customization of exercises, integration of materials, and precise evaluation using Semantic Kernel and Large Language Model. Join us in refining this innovative tool by trying the demo and sharing your feedback through our survey for continuous improvementsA Practical Guide for Beginners: Azure OpenAI with JavaScript and TypeScript (Part 03)
In this series of three articles, you will learn how to take the first steps in using Azure OpenAI Service with JavaScript and TypeScript! In this final article, let's embark on a journey from setting up Visual Studio Code to running a fully functional application interacting with AI services. Learn to configure environment variables, control conclusion generation, and achieve impressive results with Azure OpenAI and JavaScript/TypeScript. Unleash your creativity and explore deeper into artificial intelligence with our provided resources. Get ready to breathe life into your ideas!
