John Savill’s Technical Training demonstrates practical usage of Microsoft Azure Foundry’s Model Router, guiding developers on choosing and deploying optimal AI models for their applications.

Using Foundry’s Model Router to Simplify Optimal AI Model Selection

Author: John Savill’s Technical Training

Overview

This video provides a step-by-step walkthrough of Microsoft Foundry’s Model Router, aimed at simplifying the selection and deployment of the most optimal AI models in your Azure-based AI applications and agents.

Key Topics Covered

Model Dimensions: Understand various characteristics to consider when evaluating AI and language models (LLMs, SLMs) for your solutions.
Picking the Right Model: Learn how to compare and select models based on relevant criteria for your use case.
Model Router Overview: An introduction to how the Model Router service works within Microsoft Azure Foundry.
Routing Methods: Explore different strategies and options available for routing requests between models, enabling flexibility and optimization.
Deployment Steps: Guidance on deploying and configuring the Model Router in Azure, including backend model integration.
How Everything Fits Together: Visual explanation of the model selection and routing lifecycle.
Hands-On Demo: A practical demonstration of integrating and testing the Model Router with your own AI agents and applications.

Reference Materials

Additional Learning Resources

Who Should Watch

Developers building AI-powered solutions on Azure
Solution architects looking for efficient model selection and routing strategies
Anyone implementing AI agents that require flexible model deployment and management

Summary

This video provides actionable insights, technical details, and live demonstrations to help professionals optimally select and route AI models using Microsoft Azure Foundry’s Model Router component.

Enable subtitles for enhanced accessibility and translation options.