There are practical use cases for on-premises AI versus using AI in the public cloud, particularly in situations that require enhanced security, data control, and regulatory compliance. By examining these specific examples, IT professionals can gain a deeper understanding of…
Enterprise adoption of artificial intelligence (AI) has quickly evolved from experimental projects to mission-critical business drivers. Organizations across industries are now recognizing that AI is no longer a futuristic technology, but a foundational capability, required NOW, to enable innovation, efficiency,…
Repurposing existing hardware with the right infrastructure software improves IT operational efficiency by extending hardware life, reducing costs, and delivering near-bare-metal performance with high availability and resiliency.
Artificial Intelligence (AI) and Machine Learning (ML) workloads are fundamentally different from any other workload. These workloads deal in data sets measured in dozens of petabytes of capacity, and large percentages of it can go from dormant to active at…
When designing a storage infrastructure for an artificial intelligence (AI) or deep learning (DL) workload, the default assumption is that an all-flash array (AFA) or something even faster must be at the heart of the design. The problem is as…
The modern data center is increasingly microservice or container-based. These workloads are dynamic and unpredictable. The datasets within these workloads range from thousands of large files to billions of small files. Artificial Intelligence (AI) and Machine Learning (ML) are being…
Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) projects can all have varying types of data associated with them. Some projects consist of a relatively small number of huge files, and others have an incredibly high number of…
Organizations need to re-think their storage architectures for the data-driven economy. How an organization captures, stores, and analyzes data, can dictate how successful it might be in this new economic model where data drives organizations. The data-driven economy is not…
The data center, in most cases, is a mixture of legacy and modern applications that exist, both on-premises and in the cloud. To provide organizations with a competitive advantage, IT needs to use and manage these resources efficiently. IT professionals…
Network Attached Storage (NAS) systems were once the primary storage destination for all unstructured data but with file-counts soaring past one billion and with machines replacing users as the primary creators of data, the industry is seemingly moving past NAS…
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