AI Needs Specialized Storage

An episode of the Tech Field Day Podcast podcast, hosted by Tech Field Day, titled "AI Needs Specialized Storage" was published on May 17, 2022 and runs 26 minutes.

May 17, 2022 ·26m · Tech Field Day Podcast

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Summary

Given the announcements of just about every company in the industry, it appears that AI requires specialized storage to function. In this special episode, recorded prior to AI Field Day, Andy Banta and Karen Lopez join Stephen Foskett to discuss the relationship between storage, data, and AI. We’ve seen lots of companies, including AI Field Day presenters DDN, NetApp, and WEKA, selling their high-performance distributed storage solutions for AI workloads. But is this just the nature of modern storage or is it truly linked to AI systems? It seems that much of this depends on the specifics of the AI application, whether it is used for training, the size and nature of the data set, and the specific use case. We should also consider what we mean by AI. Is it image recognition, autonomous driving, or a massive data set like GPT-3 or DALL-E? Just as with all such architecture questions, the answer is it depends on the specific use case. On-Premises for Today’s Roundtable: Panelists Andy Banta Karen Lopez Moderator Stephen Foskett Twitter @AndyBanta @DataChick Twitter @SFoskett Follow us on Twitter! AND SUBSCRIBE to our newsletter for more great coverage right in your inbox.

Episode Description

Given the announcements of just about every company in the industry, it appears that AI requires specialized storage to function. In this special episode, recorded prior to AI Field Day, Andy Banta and Karen Lopez join Stephen Foskett to discuss the relationship between storage, data, and AI. We’ve seen lots of companies, including AI Field Day presenters DDN, NetApp, and WEKA, selling their high-performance distributed storage solutions for AI workloads. But is this just the nature of modern storage or is it truly linked to AI systems? It seems that much of this depends on the specifics of the AI application, whether it is used for training, the size and nature of the data set, and the specific use case. We should also consider what we mean by AI. Is it image recognition, autonomous driving, or a massive data set like GPT-3 or DALL-E? Just as with all such architecture questions, the answer is it depends on the specific use case.

On-Premises for Today’s Roundtable:

Panelists

Andy Banta

Karen Lopez

Moderator

Stephen Foskett

Twitter

@AndyBanta

@DataChick

Twitter

@SFoskett

Follow us on Twitter! AND SUBSCRIBE to our newsletter for more great coverage right in your inbox.