Introduction to Azure AI Studio

What is Azure AI Studio?

• Azure AI Studio is a unified platform that brings together various Azure AI capabilities that were previously available as standalone Azure services like Vision Studio, Document Intelligent Studio, Speech Studio, Open AI Services, Custom Vision Studio, and more.
• Azure AI Studio provides a seamless experience for developers, data scientists, and AI engineers to build, deploy, and manage AI models and applications.
• With Azure AI Studio, you can access a wide range of AI capabilities, including language models, speech, vision, and more, all in one place.

Azure AI Studio combines

• Model catalog and prompt flow development from Azure Machine Learning service.
• Generative AI model deployment, testing, and custom data integration from Azure OpenAI service.
• Integration with Azure AI Services for speech, vision, language, document intelligence, and content safety.

How does Azure AI Studio work?

Image Credit: learn.microsoft.com

AI Studio Hub

• An AI hub provides a collaborative workspace for AI solution development and management.
• You need at least one Azure AI hub to use the solution development features and capabilities of AI Studio.
• An Azure AI hub can host one or more projects.
• Each project encapsulates the tools and assets used to create a specific AI solution.

AI Studio Project

• All AI development in Azure AI Studio is performed within a project.
• When a new project is created from the hub, the security settings of the hub are applied to it.

Features of AI Studio Hub and Project
 

Hub Features

• Create members and assign them to specific roles.
• Create and manage compute instances on which to run experiments, prompt flows, and custom code.
• Create and manage connections to resources, such as data stores, GitHub, Azure AI Search indexes, and others.
• Define policies to regulate behavior, including automatic compute shutdown.

Project Features

• Deploy large language models to support a chatbot or copilot.
• Test models in the chat playground.
• Add your own data to augment prompts.
• Use prompt flow to define flows that combine models, prompts, and custom code.
• Evaluate model responses to prompts.
• Manage indexes and datasets for custom data.
• Define content filters to mitigate potentially harmful responses.
• Use Visual Studio Code in your browser to create custom code.
• Deploy solutions as web apps and containerized services.

Core Components of Azure AI Studio

• Model Catalog
• Model Benchmarks
• Prompt Catalog
• Azure OpenAI
• AI Services

Model Catalog

• Curated collection of pre-built machine learning models from Microsoft and other sources.
• Serves as a hub for discovering and utilizing a wide range of models.
• These models enable you to build generative AI applications.
• It features hundreds of models from various providers, including Azure OpenAI service, Mistral, Meta, Cohere, Nvidia, and Hugging Face.

Model Benchmarks

• Allow you to compare the performance of different models and datasets available in the industry.
• Helps in selecting the most suitable model for a particular task based on factors such as accuracy, speed, and resource consumption.

Prompt Catalog

• Collection of predefined prompts for common use cases, such as generating text or images.
• Filter prompts by
  • Modality (e.g., chat, completions, image, video)
  • Industry (e.g., retail, education)
  • Task (e.g., summarization, chat completion).

Azure OpenAI

• Provides REST API access to powerful language models, including GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, and Embedding's series.
• It can be adapted for various tasks, such as content generation, summarization, image understanding, semantic search, and natural language to code translation

AI Services

• Encompass a wide range of pre-built, customizable AI solutions.
• NLP, Computer Vision, Speech, Language, Document, Translator.
• Empower developers to create intelligent applications using out-of-the-box and customizable APIs and models.
• Developers can integrate these services via REST APIs or client library SDKs in popular programming languages.

Conclusion

Azure AI Studio stands as a powerful and intuitive platform, enabling developers and AI Engineers to harness the full potential of artificial intelligence. By bringing all standalone Azure AI Services into one platform, you can drive innovation and achieve remarkable results in your AI projects.