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Discover how Azure Storage powers OpenAI and Microsoft AI model training and end-user applications through seamless access to exabytes of unstructured data. Explore how Azure’s AI ecosystem integrates with Blob Storage through advanced features and APIs that you can use in your own AI workloads today. Learn to leverage tools like blobfuse2, Blob Connector for PyTorch, and AzCopy to optimize your training, fine-tuning and inference pipelines for both performance and cost.
To learn more, please check out these resources:
* https://github.com/Azure/azure-storage-fuse
* https://github.com/Azure/azure-storage-for-pytorch
* https://aka.ms/OpenAIcasestudy
𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀:
* Kyle Knapp
* Vishnu Charan Tumatin Jeyaprakash
𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
This is one of many sessions from the Microsoft Build 2025 event. View even more sessions on-demand and learn about Microsoft Build at https://build.microsoft.com
BRK192 | English (US) | Cloud Platform
Related Sessions:
BRK191 — https://build.microsoft.com/sessions/BRK191?wt.mc_id=yt_PLlrxD0HtieHgukvOrEw3CqZuKtxiu_wnM
BRK141 — https://build.microsoft.com/sessions/BRK141?wt.mc_id=yt_PLlrxD0HtieHgukvOrEw3CqZuKtxiu_wnM
BRK142 — https://build.microsoft.com/sessions/BRK142?wt.mc_id=yt_PLlrxD0HtieHgukvOrEw3CqZuKtxiu_wnM
#MSBuild, #CloudPlatform
Chapters:
0:00 – Overview of Azure Storage for AI Workloads
00:01:16 – Scale and Use-case of Azure Storage
00:05:54 – Exploring Scale Accounts and AI Pipeline Optimization
00:14:07 – Benchmark Results
00:26:21 – Section Overview: Installation and Key Features
00:31:02 – Explanation of fast parallel transferring with BLOB I/O
00:36:53 – Running Code Snippets to Manipulate Data Set Using Python Libraries
00:41:05 – Session Recap and Closing Notes Read More Microsoft Developer
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