AI Driven Mass-Storage Evolution
Stevens Creek
Wed Sep 17 | 3:35pm
Abstract
The extreme growth in modern AI-model training datasets, as well as the explosion of Gen-AI data output are both fueling unprecedented levels of data-storage capacity growth in the datacenters. Such rapid growth in mass-capacity is demanding evolutionary steps in foundational storage technologies to enable higher areal density, optimized data-access interface methodologies and highly efficiency power/cooling infrastructure. We will explore these evolutionary technologies and take a sneak peek at the future of mass data-storage in the AI datacenters.
Learning Objectives
Understanding the Impact of AI on Data Storage: Learn how the growth of AI-model training datasets and generative AI outputs are driving the demand for increased data storage capacity in datacenters. Exploring Evolutionary Storage Technologies: Gain insights into the advancements in storage technologies, such as higher areal density, optimized data-access interfaces, and energy-efficient infrastructure, that are addressing the challenges of mass-capacity growth. Future Trends in AI Datacenter Storage: Discover the future directions and innovations in mass data storage that will support the evolving needs of AI-driven datacenters
