Modern AI infrastructure has exposed the importance of reliability and predictability of storage in addition to performance. This episode of Utilizing Tech, presented by Solidigm, features Kelley Osburn of Graid Technology discussing the challenges of maximizing performance and resiliency of storage for AI with Jeniece Wnorowski and Stephen Foskett. AI servers are optimized for machine learning processing, and Graid Technology SupremeRAID offloads processing to GPUs similarly to the way these massively-parallel processors offload ML processing. They also have a peer-to-peer DMA feature to direct the data directly to the processor rather than forcing all data to pass through a single processor or channel. There is a need for RAID software at many spots in the data pipeline, from ingestion and preparation to processing and consolidation, and each requires performance and availability. There are many applications that require maximum performance and capacity without impacting the host CPU, including military, medical research and diagnostics, and financial, in addition to AI processing.