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โย In this session see how to build multimodal data pipelines, train and fine-tune models, and deploy them as inference services, all without managing infrastructure. Walk through the end-to-end architecture and run a live demo of building, training, and serving AI inside your Azure subscription. Anyscale on Azure is a production-ready AI platform built on a scalable stack of Ray and Azure Kubernetes Service that abstracts the complexity of distributed compute behind a Python-native interface.
๐ฆ๐ฝ๐ฒ๐ฎ๐ธ๐ฒ๐ฟ๐:
* Katarina Stanley
* Daniel Arrizza
๐ฆ๐ฒ๐๐๐ถ๐ผ๐ป ๐๐ป๐ณ๐ผ๐ฟ๐บ๐ฎ๐๐ถ๐ผ๐ป:
This is one of many sessions from the Microsoft Build 2026 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com
ODSP914 | English (US) | Working with models
Pre-recorded | (300) Advanced
#MSBuild
Chapters:
0:00 – Introduction and Session Overview by Katarina Stanley
00:00:27 – Why Teams Choose to Own Their AI Stack
00:01:31 – Challenges of Scaling AI Workloads
00:02:17 – Introduction to Ray as a Distributed Compute Framework
00:02:43 – Overview of Anyscale on Azure and Its Core Features
00:03:38 – Daniel Arrizza Demonstrates Setting Up Anyscale Cloud on Azure
00:06:02 – Exploring Workspaces, Jobs, and Services in Anyscale Console
00:10:00 – Use Case: Building a Multimodal E-commerce Recommendation Engine
00:13:01 – Fine-Tuning, Training, Embedding, and Serving with Ray
00:22:14 – Conclusion and Next Steps with QR Codes and Build Conference Infoย ย ย Read Moreย Microsoft Developerย
