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Explore the scalability and security of Azure Data Lake Storage for powering analytics and AI in this 42-minute conference talk. Learn how conventional AI models differ from Generative AI and large language models, and discover the challenges of scaling model building and inferencing. Dive into Azure Storage's integration with Azure Databricks and Microsoft Fabric to create a unified analytics platform for data engineering, data science, and machine learning. Examine the storage architecture enabling hyper-scale workloads, and understand how curated data can be utilized for Big Data Analytics, data science, business intelligence, and training GPT-X models. Gain insights into architectural patterns, real-world workload performance, and storage behavioral characteristics of large-scale workloads on Azure Storage. Presented by Jeff King and Saurabh Sensharma from Microsoft, this talk provides valuable information for those interested in leveraging Azure Data Lake Storage for scalable analytics and AI applications.
