World's Fair 2024
Multi model multimodal and multi agent innovations in Azure AI: Cedric Vidal
Overview
This talk showcases advancements in Azure AI, focusing on multimodal and multi-agent capabilities. It highlights how new models and tools, such as GPT-4o and Phi-3 Vision, can process and reason across text, vision, and speech. The presentation emphasizes practical applications and the integration of these technologies within Azure AI Studio for building sophisticated AI solutions.
Who should watch
- AI Engineers exploring multimodal AI capabilities.
- Product Managers looking to integrate advanced AI features into applications.
- Builders interested in multi-agent systems and agentic workflows.
- Developers seeking to leverage new tools for AI development and deployment.
- Anyone interested in the latest AI innovations from Microsoft Azure.
Key takeaways
- Azure AI now supports multimodal models like GPT-4o and Phi-3 Vision, enabling analysis of combined text and image inputs for tasks like menu interpretation and infrastructure monitoring.
- Video translation services can now translate videos into different languages while preserving the original speaker's intonation and tone.
- The Azure AI model catalog offers a vast selection of models, with serverless deployment options allowing pay-per-token usage, simplifying access to powerful AI.
- Phi-3 Vision, a smaller multimodal model, can run locally in the browser using WebGPU, demonstrating efficient on-device AI processing.
- Retrieval Augmented Generation (RAG) capabilities allow LLMs to access and reason over up-to-date, custom documents, enhancing information accuracy.
- Azure AI Studio provides evaluation tools to measure model performance on metrics like coherence and groundedness, crucial for RAG applications.
- Code Interpreter within Azure AI Studio can execute Python code in a sandbox to analyze complex file formats like GPX, enabling sophisticated data analysis without manual coding.
- Upcoming features like GitHub Workspaces aim to integrate LLMs directly into the development workflow for tasks such as code generation and repository analysis.
Notable quotes
*The model understands natively both pixels and text and in its internal representation has the same vectors for the same concepts.*
*This will make the world more inclusive.*
*I didn't code a single line.*
Unofficial community note. Prefer the recording for nuance.