NVMe, or Non-Volatile Memory Express, is a protocol released in 2011 for accessing high-speed storage systems media that came popular with the introduction of Solid-State Drives (SSDs). But what is NVMe and why is it important for machine learning and analytics applications? As businesses and systems continue to consume and process increasingly more data to support manufacturing, it is important to rethink how this data is captured, preserved, accessed and transformed. And because of the speed, NVMe is revolutionizing how the user configures deep learning systems for data storage, data access, and overall architecture when combined with other more traditional storage methods. This article will explain what NVMe is and share a deep technical dive into how the storage architecture works.

We believe that excellence in product delivery can only be achieved if each part of the process is standardized, optimized, and documented. To achieve this, each of our data analytics and machine learning systems is assembled following stringent internal procedures and proven quality control techniques. The figure below includes an excerpt from one of our checklists used in initial assembly stages via our technicians. Each part of the process has a similar checklist where we document critical details to ensure system quality and traceability required for any future troubleshooting/upgrades. At AI Manufacturing Solutions, we ensure that quality is part of every process we do because without quality, then the artificial intelligence algorithms our customers use may be worth less.

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