How NVIDIA's AI Data Platform and STX reference architecture are reshaping enterprise storage competition, vendor ...

Access to data that has been prepared for use in AI training, inference and other tasks is key to ensuring that storage systems don’t act as bottlenecks to full performance of GPUs and AI applications ...

Generative artificial intelligence disrupted the enterprise in 2023 and is now a must-have consideration in 2024 plans. With this in mind, technical professionals must strive to enhance and modernize ...

The BlueField-4 STX introduces the Nvidia CMX (Context Memory Storage) platform. This isn’t just “more disk,” but rather a high-performance context layer that expands GPU memory across the rack. It ...

The GPUs and accelerators at the foundation of our current AI-fueled moment need data to survive. Letting a thirty-thousand-dollar NVIDIA H100 sit idle while waiting for data is a tangible waste.

Unlock the future of industrial data. Join our webinar to compare storage systems and build a scalable architecture that ...

It’s true to say that for the public, as well as many investors, the AI revolution is a story of billion-dollar GPUs, vast amounts of compute power, and the complex (and often opaque) algorithms of ...

Pure Storage (NYSE: PSTG), a provider of all-flash data storage technologies and services, held its fourth-quarter and full-year fiscal 2025earnings callon February 26, 2025. The company discussed its ...

The AdTech world thrives on speed. Every second, billions of ad transactions take place where bids are placed, impressions are served, and data points are exchanged in a digital ballet that feels ...

Pure Storage has gathered many of its partners together to urge them to talk about data architecture and resilience as the foundations for customers moves deeper into artificial intelligence (AI). The ...

A common refrain in the tech industry is that artificial intelligence (AI) needs fast storage. While true, speed is not the only consideration when supporting the growing number of AI workloads, ...