Research Report: Impact of Storage Architecture on the AI Lifecycle
Traditional storage solutions, whether on-premises or in the cloud, often fail to meet the varying needs of each phase of the AI lifecycle. These legacy approaches are particularly ill-suited for the demands of distributed training, where keeping an expensive AI training cluster idle has a real economic impact on the enterprise.